{"version":"0.1","company":{"name":"YubHub","url":"https://yubhub.co","jobsUrl":"https://yubhub.co/jobs/skill/econometrics"},"x-facet":{"type":"skill","slug":"econometrics","display":"Econometrics","count":38},"x-feed-size-limit":100,"x-feed-sort":"enriched_at desc","x-feed-notice":"This feed contains at most 100 jobs (the most recently enriched). For the full corpus, use the paginated /stats/by-facet endpoint or /search.","x-generator":"yubhub-xml-generator","x-rights":"Free to redistribute with attribution: \"Data by YubHub (https://yubhub.co)\"","x-schema":"Each entry in `jobs` follows https://schema.org/JobPosting. YubHub-native raw fields carry `x-` prefix.","jobs":[{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_150ca1e8-f29"},"title":"Research Economist, Economic Research","description":"<p>As a Research Economist at Anthropic, you will work to measure and understand AI&#39;s effects on the global economy. You will make fundamental contributions to the development of the Anthropic Economic Index, establishing new methodologies to measure the usage, diffusion, and impact of AI throughout the economy using privacy-preserving tools and novel data sources. You will use frontier methods in econometrics, machine learning, and structural estimation. Such rigour will drive impact, shaping both policy discussions externally and informing Anthropic’s internal business and product decisions.</p>\n<p>Our team combines rigorous empirical methods with novel measurement approaches. We&#39;re building first-of-its-kind datasets tracking AI&#39;s impact on labor markets, productivity, and economic transformation. Using our privacy-preserving measurement system (Clio), we analyze millions of real-world AI interactions to understand how AI augments and automates work across different occupations and tasks.</p>\n<p>Responsibilities:</p>\n<ul>\n<li>Make fundamental contributions to the development and expansion of the Anthropic Economic Index, including quarterly reports and industry-specific deep dives</li>\n</ul>\n<ul>\n<li>Design and conduct empirical research on AI&#39;s economic effects, drawing on external data sources and the privacy-preserving measurement systems internally</li>\n</ul>\n<ul>\n<li>Develop new methodological approaches for studying AI&#39;s impact on:</li>\n</ul>\n<ul>\n<li>Labor markets and the future of work</li>\n</ul>\n<ul>\n<li>Productivity and task transformation</li>\n</ul>\n<ul>\n<li>Economic inequality and displacement</li>\n</ul>\n<ul>\n<li>Industry-specific disruption and adaptation</li>\n</ul>\n<ul>\n<li>Aggregate economic trajectories (GDP, productivity, unemployment) under varying AI-adoption scenarios</li>\n</ul>\n<ul>\n<li>Develop causal-inference tooling , e.g. surrogate indexes, heterogeneous-effect pipelines , to help Anthropic evaluate the downstream economic consequences of its own compute, product, and pricing decisions</li>\n</ul>\n<ul>\n<li>Build and maintain relationships with academic institutions, policy think tanks, and other research partners</li>\n</ul>\n<ul>\n<li>Work cross-functionally with other technical teams to improve our measurement infrastructure and data collection</li>\n</ul>\n<ul>\n<li>Translate research insights into actionable recommendations for both product decisions and policy discussions</li>\n</ul>\n<ul>\n<li>Amplify external engagement through research publications, policy briefs, and presentations to diverse stakeholders</li>\n</ul>\n<p>You May Be a Good Fit If You Have:</p>\n<ul>\n<li>PhD in Economics</li>\n</ul>\n<ul>\n<li>Strong track record of empirical research, particularly studies combining novel data sources and economic theory or those implementing frontier methods in causal inference and machine learning</li>\n</ul>\n<ul>\n<li>Experience relevant to the study of AI’s impact on the economy, including:</li>\n</ul>\n<ul>\n<li>Labor market analysis and occupational change</li>\n</ul>\n<ul>\n<li>Task-based approaches to technological transformation</li>\n</ul>\n<ul>\n<li>Large-scale data analysis and econometric methods</li>\n</ul>\n<ul>\n<li>Large language models for social science research</li>\n</ul>\n<ul>\n<li>Policy-relevant economic research</li>\n</ul>\n<ul>\n<li>Experimental and quasi-experimental methods for causal inference</li>\n</ul>\n<ul>\n<li>Macroeconomic modeling and time series forecasting</li>\n</ul>\n<ul>\n<li>Agent-based modeling or large-scale simulation</li>\n</ul>\n<ul>\n<li>Technical skills including:</li>\n</ul>\n<ul>\n<li>Proficiency in Python, R, SQL, or similar tools for large-scale data analysis</li>\n</ul>\n<ul>\n<li>Experience working with novel datasets and measurement systems</li>\n</ul>\n<ul>\n<li>Comfort learning new technical tools and frameworks</li>\n</ul>\n<ul>\n<li>Demonstrated ability to:</li>\n</ul>\n<ul>\n<li>Lead complex research projects from conception to publication</li>\n</ul>\n<ul>\n<li>Communicate technical findings to diverse audiences</li>\n</ul>\n<ul>\n<li>Build relationships across academic, policy, and industry communities</li>\n</ul>\n<ul>\n<li>Strong interest in ensuring AI development benefits humanity</li>\n</ul>\n<ul>\n<li>Comfort working with AI systems and ability to think critically about their capabilities and limitations</li>\n</ul>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a 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Your expertise in quantitative modeling, experimentation, and algorithms will be utilized to solve complex engineering challenges. You&#39;ll collaborate with cross-functional partners across Product, Engineering, Design, Research, Product Analytics, Data Engineering, and others to drive product development and introduce scientific rigor into real-world products serving hundreds of millions of users.</p>\n<p>Key responsibilities include:</p>\n<ul>\n<li>Developing best practices for instrumentation and experimentation to help fulfill our mission to bring everyone the inspiration to create a life they love</li>\n<li>Bringing scientific rigor and statistical methods to the challenges of product creation, development, and improvement with an appreciation for the behaviors of our users</li>\n<li>Building and prototyping analysis pipelines iteratively to provide insights at scale while developing comprehensive knowledge of data structures and metrics, advocating for changes where needed for product development</li>\n<li>Working cross-functionally to build and communicate key insights, and collaborating closely with product managers, engineers, designers, and researchers to help build the next experiences on Pinterest</li>\n</ul>\n<p>Requirements include:</p>\n<ul>\n<li>5+ years of experience analyzing data in a fast-paced, data-driven environment with proven ability to apply scientific methods to solve real-world problems on web-scale data</li>\n<li>Extensive experience solving analytical problems using quantitative approaches, including machine learning, statistical modeling, forecasting, econometrics, or other related fields</li>\n<li>Experience using machine learning and deep learning frameworks, such as PyTorch, TensorFlow, or scikit-learn</li>\n<li>A scientifically rigorous approach to analysis and data, and a well-tuned sense of skepticism, attention to detail, and commitment to high-quality, results-oriented output</li>\n<li>Ability to manipulate large data sets with high dimensionality and complexity; fluency in SQL (or other database languages) and a scripting language (Python or R)</li>\n<li>Excellent communication skills and ability to explain learnings to both technical and non-technical partners</li>\n<li>A team player who&#39;s able to partner with cross-functional leadership to quickly turn insights into actions</li>\n</ul>\n<p>Relocation assistance is not eligible for this position. The base salary range for this position is $139,764-$287,749 USD, and the position is eligible for equity.</p>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_7c809f8b-e66","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Pinterest","sameAs":"https://www.pinterest.com/","logo":"https://logos.yubhub.co/pinterest.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/pinterest/jobs/6087213","x-work-arrangement":"hybrid","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$139,764-$287,749 USD","x-skills-required":["Quantitative modeling","Experimentation","Algorithms","Machine learning","Statistical modeling","Forecasting","Econometrics","SQL","Python","R"],"x-skills-preferred":[],"datePosted":"2026-04-18T15:57:11.326Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco, CA, US; Remote, US"}},"jobLocationType":"TELECOMMUTE","employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Quantitative modeling, Experimentation, Algorithms, Machine learning, Statistical modeling, Forecasting, Econometrics, SQL, Python, R","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":139764,"maxValue":287749,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_4fde2d89-11c"},"title":"Research Engineer, Economic Research","description":"<p>As a Research Engineer on the Economic Research team, you will design, build, and maintain critical infrastructure that powers Anthropic&#39;s research on AI&#39;s economic impact. You will work with data systems from across Anthropic, including our research tools for privacy-preserving analysis.\\n\\nThe Economic Research team at Anthropic studies the economic implications of AI on individual, firm, and economy-wide outcomes. We build scalable systems to monitor AI usage patterns and directly measure the impact of AI adoption on real-world outcomes. We publish research and data that is clear-eyed about the economic effects of AI to help policymakers, businesses, and the public understand and navigate the transition to powerful AI.\\n\\nIn this role, you will work closely with teams across Anthropic,including Data Science and Analytics, Data Infrastructure, Societal Impacts, and Public Policy,to build scalable and robust data systems that support high-leverage, high-impact research. Strong candidates will have a track record building data processing pipelines, architecting &amp; implementing high-quality internal infrastructure, working in a fast-paced startup environment, navigating ambiguity, and demonstrating an eagerness to develop their own research &amp; technical skills.\\n\\nResponsibilities:\\n\\n<em> Build and maintain data pipelines that process large scale Claude usage logs into canonical, reusable datasets while maintaining user privacy.\\n</em> Expand privacy-preserving tools to enable new analytic functionality to support research needs.\\n<em> Design and implement novel data systems leveraging language models (e.g., CLIO) where traditional software engineering patterns don&#39;t yet exist.\\n</em> Develop and maintain data pipelines that are interoperable across data sources (including ingesting external data) and are designed to support economic analysis.\\n<em> Contribute to the strategic development of the economic research data foundations roadmap\\n</em> Ensure data reliability, integrity, and privacy compliance across all economic research data infrastructure\\n<em> Lead technical design discussions to ensure our infrastructure can support both current needs and future research directions\\n</em> Create documentation and best practices that enable self-serve data access for researchers while maintaining security and governance standards.\\n<em> Partner closely with researchers, data scientists, policy experts, and other cross-functional partners to advance Anthropic’s safety mission\\n\\nYou might be a good fit if you have:\\n\\n</em> Experience working with Research Scientists and Economists on ambiguous AI and economic projects\\n<em> Experience with building and maintaining data infrastructure, large datasets, and internal tools in production environments.\\n</em> Experience with cloud infrastructure platforms such as AWS or GCP.\\n<em> Take pride in writing clean, well-documented code in Python that others can build upon\\n</em> Are comfortable making technical decisions with incomplete information while maintaining high engineering standards\\n<em> Are comfortable getting up-to-speed quickly on unfamiliar codebases, and can work well with other engineers with different backgrounds across the organization\\n</em> Have a track record of using technical infrastructure to interface effectively with machine learning models\\n<em> Have experience deriving insights from imperfect data streams\\n</em> Have experience building systems and products on top of LLMs\\n<em> Have experience incubating and maturing tooling platforms used by a wide variety of stakeholders\\n</em> A passion for Anthropic&#39;s mission of building helpful, honest, and harmless AI and understanding its economic implications.\\n<em> A “full-stack mindset”, not hesitating to do what it takes to solve a problem end-to-end, even if it requires going outside the original job description.\\n</em> Strong communication skills to collaborate effectively with economists, researchers, and cross-functional partners who may have varying levels of technical expertise.\\n\\nStrong candidates may have:\\n\\n<em> Background in econometrics, statistics, or quantitative social science research\\n</em> Experience building data infrastructure and data foundations for research\\n<em> Familiarity with large language models, AI systems, or ML research workflows\\n</em> Prior work on projects related to labor economics, technology adoption, or economic measurement\\n\\nSome Examples of Our Recent Work\\n\\n<em> Anthropic Economic Index Report: Economic Primitives\\n</em> Anthropic Economic Index Report: Uneven Geographic and Enterprise AI Adoption\\n<em> Estimating AI productivity gains from Claude conversations\\n</em> The Anthropic Economic Index\\n\\nDeadline to apply: None. Applications are reviewed on a rolling basis\\n\\nThe annual compensation range for this role is listed below.\\n\\nFor sales roles, the range provided is the role’s On Target Earnings (&quot;OTE&quot;) range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.\\n\\nAnnual Salary: $300,000-$405,000 USD\\n\\nLogistics\\n\\nMinimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience\\nRequired field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience\\nMinimum years of experience: Years of experience required will correlate with the internal job level requirements for the position\\nLocation-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.\\nVisa sponsorship: We do sponsor visas! However, we aren&#39;t able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.\\n\\nWe encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you&#39;re interested in this work. We think AI systems like the ones we&#39;re building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.\\n\\nYour safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you&#39;re ever unsure about a communication, don&#39;t click any links,visit anthropic.com/careers directly for confirmed position openings.\\n\\nHow we&#39;re different\\n\\nWe believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. 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This role will sit under the Advanced Analytics family and support Product and Business leaders within our CS Safety organisation.</p>\n<p>As a Staff Advanced Analyst, you will be a data thought partner to product and business leaders across teams through providing insights, recommendations, and enabling data-informed decisions. You will drive day-to-day analytics and create scalable data tools, identify pain points in travelling and hosting, and work with product leadership to improve experiences for our guest, host, and agent community.</p>\n<p>In addition, you will leverage Airbnb&#39;s rich and unique data, state-of-the-art machine learning infrastructure, and other central data science tools to build and grow the measurement capacity within the organisation. You will also be deeply involved in the technical details of the various systems we build, and will have the opportunity to collaborate with a strong team of engineers, product managers, designers, and operations agents to achieve shared, cross-functional goals to help keep Airbnb&#39;s community safe and trusted.</p>\n<p>Key responsibilities include:</p>\n<ul>\n<li>Leading and driving data-driven roadmaps for the CS Safety working groups</li>\n<li>Recommending actionable solutions backed by data and metrics to product and operational problems</li>\n<li>Building and owning an insights and reporting platform that measures and improves the effectiveness of behaviours, product interfaces, and processes across the CS Safety platform and contact centre network</li>\n<li>Performing data modelling of the various entities using tools and frameworks for optimising community and agent experiences</li>\n<li>Defining and evaluating key metrics in an unstructured problem space, including measurement of the ML models that drive product development</li>\n<li>Anticipating emerging safety risks through early-warning indicators, trend analysis, predictive modelling, and scenario planning to assess operational risk</li>\n<li>Influencing data-driven decisions across business verticals in day-to-day via business reviews, scorecards, self-serve portal, OKRs, and planning among others</li>\n<li>Influencing experimentation and measurement strategies; conducting power analyses, defining exit criteria, and using statistical models to improve inference</li>\n</ul>\n<p>Requirements include:</p>\n<ul>\n<li>A minimum of 10+ years of industry experience in business analytics and a degree (Masters or PhD) in a quantitative field (e.g., Statistics, Econometrics, Computer Science, Engineering, Mathematics, Data Science, Operations Research)</li>\n<li>Experience supporting safety, risk, Trust &amp; Safety, compliance, or employee wellbeing in high-volume call centre or customer operations environments</li>\n<li>Expert skills in SQL and expert in at least one programming language for data analysis (Python or R)</li>\n<li>Experience with non-experimental causal inference methods, experimentation, and machine learning techniques, ideally in a multi-sided platform setting</li>\n<li>Working knowledge of schema design and high-dimensional data modelling (ETL framework like Airflow)</li>\n<li>Ability to work under conditions of ambiguity in a fast-growth, sometimes uncertain and complex environment</li>\n<li>Comfortable operating independently with minimal planning, direction, and supervision</li>\n<li>Proven track record of influencing senior leaders and driving outcomes</li>\n</ul>\n<p>Experience Level: Staff Employment Type: Full-time Workplace Type: Remote Category: Engineering Industry: Technology Salary Range: $176,000-$220,000 USD Required Skills: SQL, Python, R, Machine Learning, Data Analysis, Data Modelling, Causal Inference, Experimentation, Statistical Models Preferred Skills: Data Science, Operations Research, Statistics, Econometrics, Computer Science, Engineering, Mathematics</p>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_3ff860ce-94c","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Airbnb","sameAs":"https://www.airbnb.com/","logo":"https://logos.yubhub.co/airbnb.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/airbnb/jobs/7579193","x-work-arrangement":"remote","x-experience-level":"staff","x-job-type":"full-time","x-salary-range":"$176,000-$220,000 USD","x-skills-required":["SQL","Python","R","Machine Learning","Data Analysis","Data Modelling","Causal Inference","Experimentation","Statistical Models"],"x-skills-preferred":["Data Science","Operations Research","Statistics","Econometrics","Computer Science","Engineering","Mathematics"],"datePosted":"2026-04-18T15:47:55.305Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"United States"}},"jobLocationType":"TELECOMMUTE","employmentType":"FULL_TIME","occupationalCategory":"engineering","industry":"technology","skills":"SQL, Python, R, Machine Learning, Data Analysis, Data Modelling, Causal Inference, Experimentation, Statistical Models, Data Science, Operations Research, Statistics, Econometrics, Computer Science, Engineering, Mathematics","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":176000,"maxValue":220000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_2bf29bb5-f9d"},"title":"Research Engineer, Economic Research","description":"<p>As a Research Engineer on the Economic Research team, you will design, build, and maintain critical infrastructure that powers Anthropic&#39;s research on AI&#39;s economic impact. You will work with data systems from across Anthropic, including our research tools for privacy-preserving analysis.\\n\\nThe Economic Research team at Anthropic studies the economic implications of AI on individual, firm, and economy-wide outcomes. We build scalable systems to monitor AI usage patterns and directly measure the impact of AI adoption on real-world outcomes. We publish research and data that is clear-eyed about the economic effects of AI to help policymakers, businesses, and the public understand and navigate the transition to powerful AI.\\n\\nIn this role, you will work closely with teams across Anthropic,including Data Science and Analytics, Data Infrastructure, Societal Impacts, and Public Policy,to build scalable and robust data systems that support high-leverage, high-impact research. Strong candidates will have a track record building data processing pipelines, architecting &amp; implementing high-quality internal infrastructure, working in a fast-paced startup environment, navigating ambiguity, and demonstrating an eagerness to develop their own research &amp; technical skills.\\n\\nResponsibilities:\\n\\n<em> Build and maintain data pipelines that process large scale Claude usage logs into canonical, reusable datasets while maintaining user privacy.\\n</em> Expand privacy-preserving tools to enable new analytic functionality to support research needs.\\n<em> Design and implement novel data systems leveraging language models (e.g., CLIO) where traditional software engineering patterns don&#39;t yet exist.\\n</em> Develop and maintain data pipelines that are interoperable across data sources (including ingesting external data) and are designed to support economic analysis.\\n<em> Contribute to the strategic development of the economic research data foundations roadmap\\n</em> Ensure data reliability, integrity, and privacy compliance across all economic research data infrastructure\\n<em> Lead technical design discussions to ensure our infrastructure can support both current needs and future research directions\\n</em> Create documentation and best practices that enable self-serve data access for researchers while maintaining security and governance standards.\\n<em> Partner closely with researchers, data scientists, policy experts, and other cross-functional partners to advance Anthropic’s safety mission\\n\\nYou might be a good fit if you have:\\n\\n</em> Experience working with Research Scientists and Economists on ambiguous AI and economic projects\\n<em> Experience with building and maintaining data infrastructure, large datasets, and internal tools in production environments.\\n</em> Experience with cloud infrastructure platforms such as AWS or GCP.\\n<em> Take pride in writing clean, well-documented code in Python that others can build upon\\n</em> Are comfortable making technical decisions with incomplete information while maintaining high engineering standards\\n<em> Are comfortable getting up-to-speed quickly on unfamiliar codebases, and can work well with other engineers with different backgrounds across the organization\\n</em> Have a track record of using technical infrastructure to interface effectively with machine learning models\\n<em> Have experience deriving insights from imperfect data streams\\n</em> Have experience building systems and products on top of LLMs\\n<em> Have experience incubating and maturing tooling platforms used by a wide variety of stakeholders\\n</em> A passion for Anthropic&#39;s mission of building helpful, honest, and harmless AI and understanding its economic implications.\\n<em> A “full-stack mindset”, not hesitating to do what it takes to solve a problem end-to-end, even if it requires going outside the original job description.\\n</em> Strong communication skills to collaborate effectively with economists, researchers, and cross-functional partners who may have varying levels of technical expertise.\\n\\nStrong candidates may have:\\n\\n<em> Background in econometrics, statistics, or quantitative social science research\\n</em> Experience building data infrastructure and data foundations for research\\n<em> Familiarity with large language models, AI systems, or ML research workflows\\n</em> Prior work on projects related to labor economics, technology adoption, or economic measurement\\n\\nSome Examples of Our Recent Work\\n\\n<em> Anthropic Economic Index Report: Economic Primitives\\n</em> Anthropic Economic Index Report: Uneven Geographic and Enterprise AI Adoption\\n<em> Estimating AI productivity gains from Claude conversations\\n</em> The Anthropic Economic Index\\n\\nDeadline to apply: None. Applications are reviewed on a rolling basis\\n\\nThe annual compensation range for this role is listed below.\\n\\nFor sales roles, the range provided is the role’s On Target Earnings (&quot;OTE&quot;) range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.\\n\\nAnnual Salary: $300,000-$405,000 USD\\n\\nLogistics\\n\\nMinimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience\\nRequired field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience\\nMinimum years of experience: Years of experience required will correlate with the internal job level requirements for the position\\nLocation-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.\\nVisa sponsorship: We do sponsor visas! However, we aren&#39;t able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.\\n\\nWe encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you&#39;re interested in this work. We think AI systems like the ones we&#39;re building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.\\n\\nYour safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you&#39;re ever unsure about a communication, don&#39;t click any links,visit anthropic.com/careers directly for confirmed position openings.\\n\\nHow we&#39;re different\\n\\nWe believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact , advancing our long-term goals of steerable, trustworthy AI , rather than work on small\\n</p>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_2bf29bb5-f9d","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Anthropic","sameAs":"https://www.anthropic.com/","logo":"https://logos.yubhub.co/anthropic.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/anthropic/jobs/5071132008","x-work-arrangement":"hybrid","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$300,000-$405,000 USD","x-skills-required":["Python","Cloud infrastructure platforms (AWS or GCP)","Data infrastructure","Large datasets","Internal tools","Machine learning models","Language models (LLMs)","Econometrics","Statistics","Quantitative social science research"],"x-skills-preferred":["Full-stack mindset","Strong communication skills","Ambiguity tolerance","Research and development","Incubating and maturing tooling platforms"],"datePosted":"2026-04-18T15:41:59.099Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco, CA"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Python, Cloud infrastructure platforms (AWS or GCP), Data infrastructure, Large datasets, Internal tools, Machine learning models, Language models (LLMs), Econometrics, Statistics, Quantitative social science research, Full-stack mindset, Strong communication skills, Ambiguity tolerance, Research and development, Incubating and maturing tooling platforms","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":300000,"maxValue":405000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_f77be5b8-7b6"},"title":"Finance Expert - Risk","description":"<p>As a Finance Risk Expert at xAI, you will play a crucial role in advancing our cutting-edge AI systems by providing high-quality annotations, expert evaluations, and detailed risk reasoning using specialized labeling tools.</p>\n<p>You will collaborate closely with technical teams to support the development and refinement of new AI capabilities, with a primary focus on quantitative financial risk management domains. Your expertise will drive the selection and rigorous resolution of complex risk-related problems, including market risk modeling, credit and counterparty risk, liquidity and funding risk, operational and model risk, stress testing &amp; scenario analysis, Value at Risk (VaR)/Expected Shortfall (ES), risk attribution, capital allocation (economic/regulatory), and enterprise-wide risk frameworks under regulatory regimes (Basel, Dodd-Frank, IFRS 9, etc.).</p>\n<p>This role requires exceptional quantitative rigor, rapid adaptation to evolving guidelines, and the ability to deliver precise, technically sound critiques, derivations, and solutions in a fast-paced environment. As a Finance Risk Expert, you will directly support xAI&#39;s mission by helping train and refine frontier AI models. You will teach the models how risk professionals quantify uncertainties, model tail events, assess portfolio vulnerabilities, ensure regulatory compliance, perform stress testing, and make data-driven decisions to protect capital and maintain financial stability.</p>\n<p>Your tasks may include recording audio walkthroughs of risk models, participating in video-based scenario reasoning, or producing detailed quantitative risk analysis traces. All outputs are considered work-for-hire and owned by xAI.</p>\n<p>Responsibilities:</p>\n<ul>\n<li>Use proprietary annotation and evaluation software to deliver accurate labels, rankings, critiques, and comprehensive solutions on assigned projects</li>\n<li>Consistently produce high-quality, curated data that adheres to strict quantitative and regulatory standards</li>\n<li>Collaborate with engineers and researchers to develop and iterate on new training tasks, risk-specific benchmarks, and evaluation frameworks</li>\n<li>Provide constructive feedback to improve the efficiency, precision, and usability of annotation and data-collection tools</li>\n<li>Select and solve challenging problems from financial risk domains where you have deep expertise</li>\n</ul>\n<p>Basic Qualifications:</p>\n<ul>\n<li>Master’s or PhD in a quantitative discipline: Quantitative Finance, Financial Engineering, Financial Mathematics, Statistics, Applied Mathematics, Econometrics, Risk Management, Operations Research, Physics, Computer Science (with risk/finance focus), or closely related field or equivalent professional experience as a quantitative risk analyst, risk modeler, or risk quant</li>\n<li>Excellent written and verbal English communication (technical reports, regulatory documentation, explanatory breakdowns)</li>\n<li>Strong familiarity with financial risk data sources and platforms (Bloomberg, Refinitiv, Moody’s Analytics, S&amp;P Capital IQ, RiskMetrics, internal bank risk systems, regulatory filings, Basel/FRB datasets, etc.)</li>\n<li>Exceptional analytical reasoning, attention to detail, and ability to exercise sound judgment with incomplete or ambiguous data</li>\n</ul>\n<p>Preferred Skills and Experience:</p>\n<ul>\n<li>Professional experience in quantitative risk management, model development/validation, or risk analytics at a bank, hedge fund, asset manager, insurance company, regulator, or consulting firm</li>\n<li>Track record of publication(s) or contributions in 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offered as full-time, part-time, or contractor positions, depending on role needs and candidate fit</li>\n<li>For contractor positions, hours will vary widely based on project scope and contractor availability, with no fixed commitments required</li>\n<li>Tutor roles may be performed remotely from any location worldwide, subject to legal eligibility, time-zone compatibility, and role specific needs</li>\n<li>For US based candidates, please note we are unable to hire in the states of Wyoming and Illinois at this time</li>\n<li>We are unable to provide visa sponsorship</li>\n<li>For those who will be working from a personal device, your computer must meet xAI’s minimum hardware requirements</li>\n</ul>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a 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pipelines"},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_8312ed9a-4ae"},"title":"Macro & Credit Research Economist","description":"<p>We believe that the way people interact with their finances will drastically improve in the next few years. We&#39;re dedicated to empowering this transformation by building the tools and experiences that thousands of developers use to create their own products.</p>\n<p>Plaid powers the tools millions of people rely on to live a healthier financial life. We work with thousands of companies like Venmo, SoFi, several of the Fortune 500, and many of the largest banks to make it easy for people to connect their financial accounts to the apps and services they want to use.</p>\n<p>The Macro &amp; Economic Insights team is responsible for translating Plaid&#39;s unique, high-frequency transaction and balance data into rigorous, forward-looking insights about household financial health, credit dynamics, and the broader economic cycle.</p>\n<p>As the Macro and Credit Research Economist, you will build and own macroeconomic and credit indicators derived directly from raw transaction data. You will develop forecasting models, identify economic turning points, and produce rigorous analysis that informs internal decisions and external research.</p>\n<p><strong>Responsibilities:</strong></p>\n<ul>\n<li>Work directly with large-scale, messy transaction data to build the transformations, filters, and statistical frameworks needed to extract reliable economic and credit-cycle signals.</li>\n<li>Develop forecasting models that quantify household financial conditions, credit dynamics, and broader economic trends, emphasizing real-world performance and interpretability.</li>\n<li>Identify leading indicators and turning points across liquidity, spending patterns, credit behavior, income stability, and other elements of household financial resilience.</li>\n<li>Build methodologies that detect changes in economic regimes and risk conditions based on high-frequency data.</li>\n<li>Produce rigorous backtests, scenarios, and real-time indicators that inform internal strategic decisions and external-facing research.</li>\n<li>Create investor-grade written analyses, dashboards, and periodic briefings that synthesize model outputs with clear economic context.</li>\n<li>Benchmark internal measures against official statistics and market expectations, highlighting where Plaid&#39;s data provides differentiated early insight.</li>\n<li>Collaborate with product, policy, comms, and GTM teams to shape how selected findings inform data products, strategic narratives, and outreach.</li>\n</ul>\n<p><strong>Qualifications:</strong></p>\n<ul>\n<li>PhD in Economics (macro, finance, monetary, applied micro) or an equivalent quantitative field.</li>\n<li>4-8 years of applied experience in macro strategy, credit investing, systematic research, or consumer credit analytics.</li>\n<li>Strong econometric and time-series modeling skills, with experience linking micro data to macro outcomes.</li>\n<li>Proficiency in Python and SQL, with comfort working directly with large, noisy, high-frequency datasets.</li>\n<li>Ability to independently build data pipelines and handle raw transaction data, rather than relying on pre-curated macroeconomic datasets.</li>\n<li>Strong written communication skills suitable for investor and executive audiences.</li>\n</ul>\n<p><strong>Preferred Qualifications:</strong></p>\n<ul>\n<li>Preferred Experience in hedge funds, asset management, credit investing, central bank research, or fintech risk teams.</li>\n<li>Familiarity with consumer credit behavior, household finance, and unsecured lending cycles.</li>\n<li>Track record of forecasting under uncertainty with measurable performance.</li>\n<li>Experience producing research or insights that influenced investment decisions or risk assessments</li>\n</ul>\n<p><strong>Additional Information</strong></p>\n<p>Our mission at Plaid is to unlock financial freedom for everyone. To support that mission, we seek to build a diverse team of driven individuals who care deeply about making the financial ecosystem more equitable. We recognize that strong qualifications can come from both prior work experiences and lived experiences. We encourage you to apply to a role even if your experience doesn&#39;t fully match the job description. We are always looking for team members that will bring something unique to Plaid!</p>\n<p>Plaid is proud to be an equal opportunity employer and values diversity at our company. We do not discriminate based on race, color, national origin, ethnicity, religion or religious belief, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, military or veteran status, disability, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state, and local laws. Plaid is committed to providing reasonable accommodations for candidates with disabilities in our recruiting process. If you need any assistance with your application or interviews due to a disability, please let us know at accommodations@plaid.com.</p>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_8312ed9a-4ae","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Plaid","sameAs":"https://plaid.com/","logo":"https://logos.yubhub.co/plaid.com.png"},"x-apply-url":"https://jobs.lever.co/plaid/582b1c72-e531-4e71-ba80-09956c1163eb","x-work-arrangement":"hybrid","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$226,800-$315,600 per year","x-skills-required":["Econometrics","Time-series modeling","Python","SQL","Data('../../../pipelines","Raw transaction data"],"x-skills-preferred":["Hedge funds","Asset management","Credit investing","Central bank research","Fintech risk teams"],"datePosted":"2026-04-17T12:52:10.547Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Econometrics, Time-series modeling, Python, SQL, Data('../../../pipelines, Raw transaction data, Hedge funds, Asset management, Credit investing, Central bank research, Fintech risk teams","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":226800,"maxValue":315600,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_a110b4b9-802"},"title":"Security Modeling - Associate","description":"<p><strong>About this role</strong></p>\n<p>We are seeking an Associate Quantitative Modeler to join the Securitized Products Modeling team within Aladdin Financial Engineering (AFE) - Single Security. The team is responsible for the development, enhancement, and governance of models and analytics across a broad range of securitized products, including Agency MBS, NonAgency RMBS, CRT, MSR, CMBS/CRE, ABS/ABF, and CLOs, delivered on the Aladdin platform to internal portfolio teams and external clients.</p>\n<p><strong>Key Responsibilities</strong></p>\n<ul>\n<li>Develop, enhance, and maintain securitized products models using econometric and machine-learning/AI techniques.</li>\n<li>Collaborate with Data, Technology, Portfolio Management, Client, and Risk teams to ensure analytics meet business and client needs.</li>\n<li>Clearly communicate modeling frameworks, assumptions, and results to both technical and non-technical audiences; support client discussions by explaining complex analytics and modeling concepts in a clear, intuitive, and practical manner.</li>\n<li>Perform rigorous validation of model inputs and outputs across development, implementation, and production environments.</li>\n<li>Play a key role in model risk management, controls, and regulatory compliance; own model performance monitoring frameworks and engage with governance forums.</li>\n<li>Identify opportunities to automate, streamline, and scale analytical and reporting processes across the modeling platform, enhancing monitoring and reporting workflows through the creative design of tools and applications, including modern AI-enabled technologies.</li>\n</ul>\n<p><strong>Qualifications</strong></p>\n<ul>\n<li>3-4 years of hands-on experience in quantitative model development and implementation.</li>\n<li>Strong quantitative background with a degree in Computer Science, Engineering, Mathematics, Statistics, Economics, or a related field.</li>\n<li>Proficient programming skills in Python, R (or equivalent); C++ familiarity is a plus.</li>\n<li>Strong communication skills and ability to explain complex analytics clearly.</li>\n<li>Experience with large datasets, production-level analytics, or financial modeling platforms is a plus.</li>\n<li>Knowledge of securitized products is a plus but not required.</li>\n</ul>\n<p><strong>Our benefits</strong></p>\n<p>To help you stay energized, engaged and inspired, we offer a wide range of employee benefits including: retirement investment and tools designed to help you in building a sound financial future; access to education reimbursement; comprehensive resources to support your physical health and emotional well-being; family support programs; and Flexible Time Off (FTO) so you can relax, recharge and be there for the people you care about.</p>\n<p><strong>Our hybrid work model</strong></p>\n<p>BlackRock’s hybrid work model is designed to enable a culture of collaboration and apprenticeship that enriches the experience of our employees, while supporting flexibility for all. Employees are currently required to work at least 4 days in the office per week, with the flexibility to work from home 1 day a week. Some business groups may require more time in the office due to their roles and responsibilities. We remain focused on increasing the impactful moments that arise when we work together in person – aligned with our commitment to performance and innovation. As a new joiner, you can count on this hybrid model to accelerate your learning and onboarding experience here at BlackRock.</p>\n<p><strong>About BlackRock</strong></p>\n<p>At BlackRock, we are all connected by one mission: to help more and more people experience financial well-being. Our clients, and the people they serve, are saving for retirement, paying for their children’s educations, buying homes and starting businesses. Their investments also help to strengthen the global economy: support businesses small and large; finance infrastructure projects that connect and power cities; and facilitate innovations that drive progress.</p>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_a110b4b9-802","directApply":true,"hiringOrganization":{"@type":"Organization","name":"BlackRock","sameAs":"https://jobs.workable.com","logo":"https://logos.yubhub.co/view.com.png"},"x-apply-url":"https://jobs.workable.com/view/dzUuaCMhjeC95Q6KURGec5/security-modeling---associate-in-london-at-blackrock","x-work-arrangement":"hybrid","x-experience-level":"mid","x-job-type":"full-time","x-salary-range":null,"x-skills-required":["Python","R","C++","Machine learning","AI","Econometrics","Data analysis","Model development","Model risk management"],"x-skills-preferred":["Data science","Statistics","Mathematics","Computer science"],"datePosted":"2026-03-09T16:44:37.495Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"London"}},"employmentType":"FULL_TIME","occupationalCategory":"Finance","industry":"Finance","skills":"Python, R, C++, Machine learning, AI, Econometrics, Data analysis, Model development, Model risk management, Data science, Statistics, Mathematics, Computer science"},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_ce4cfdc4-06d"},"title":"Senior Media Manager","description":"<p><strong>Who We Are  Zoopla is a leading UK property website with over nine million monthly users, empowering movers to make better property decisions. As a trusted consumer brand, we&#39;re more than just a property portal - we&#39;re a pipeline of movers for our customers (estate agents and housebuilders).  ## What You&#39;ll Do  As Senior Media Manager, you&#39;ll take full ownership of our Above The Line (ATL) brand media budget, acting as the primary strategic lead for our agency relationship with Zenith. You&#39;ll report to the Brand Marketing Lead but also work in lockstep with our Head of Digital Marketing and in-house Performance Marketing Manager.  This is a high-impact role requiring a &quot;challenger brand&quot; mentality. You&#39;ll be responsible for making every pound of our multi-million pound media budget work harder than the competition through relentless optimisation, sophisticated modeling, and persuasive stakeholder management.  ## On a Daily Basis  - <strong>Strategic Media Ownership</strong>: Lead the briefing, planning, and activation of all consumer-facing brand media (TV, VOD, OOH, Audio, etc.). 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You&#39;ll leverage econometrics, media modeling, and brand tracking to prove KPI impact and ROI. - <strong>Media Budget Optimisation</strong>: Manage and optimise brand media budgets with extreme detail-orientation, ensuring maximum efficiency and best practice tactics for a challenger brand. Hunting opportunities to use AI to make your planning faster, better, more impactful. - <strong>Stakeholder Influence</strong>: Manage and persuade C-suite stakeholders, translating complex media data into concise, simple but compelling narratives that drive business decisions.  ## Who You Are  - A proven track record (8+ years) building brand marketing, media, and campaign efforts, ideally for another marketplace or technology brand. - A strong knowledge of growing brands through media. You have confidence and experience in owning media direction and execution through a full breadth of brand channel and media partnerships. - ROI-minded, using data and measurement to inform and justify every pound to spend. You have a LinkedIn full of media owner relationships and you love negotiating media deals that drive cost-effective brand impact. - Totally confident in managing external agencies, continuously interrogating media plans to ensure you are comfortable with every channel, forecast, and pound on the plan. - Thrive in fast-paced environments that require flexibility and regular sharing across different levels of stakeholders. You&#39;re an excellent communicator with strong verbal and written skills, happy to present work at any moment. - Proactive and humble but also extremely passionate about your craft, with a solutions-driven mindset and sense of pride and responsibility to work hand-in and deliver great results with the wider Marketing team.  ## Where You&#39;ll Be  At Zoopla, we embrace hybrid working but emphasise the importance of also spending time together. You&#39;ll have the opportunity to work remotely (at home) for two days per week with Mondays and Thursdays as all-Zoopla days in the office together plus a third in-office day of your choosing.  Our home in Tower Bridge is a wonderful hub for collaborative and individual working, with space to socialise and exercise. On our doorstep, you&#39;ll find buzzing Borough, Bankside, and Bermondsey, not to mention soaring river views.  ## Benefits  - 25 days annual leave + extra days for years of service - Day off for volunteering &amp; Digital detox day - Festive Closure - business closed for period between Christmas and New Year - Cycle to work and electric car schemes - Free Calm App membership - Enhanced Parental leave - Fertility Treatment Financial Support - Group Income Protection and private medical insurance - Gym on-site in London - 7.5% pension contribution by the company - Discretionary annual bonus up to 10% of base salary</strong></p>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_ce4cfdc4-06d","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Zoopla","sameAs":"https://apply.workable.com","logo":"https://logos.yubhub.co/j.com.png"},"x-apply-url":"https://apply.workable.com/j/08BF494BE2","x-work-arrangement":"hybrid","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":null,"x-skills-required":["Media planning","Media buying","Media optimisation","Data analysis","Stakeholder management","Agency management","Digital marketing","Brand marketing","ROI measurement"],"x-skills-preferred":["AI planning","Econometrics","Media modeling","Brand tracking","LinkedIn","Media owner relationships","Negotiation"],"datePosted":"2026-03-09T16:04:50.775Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"London"}},"employmentType":"FULL_TIME","occupationalCategory":"Marketing","industry":"Technology","skills":"Media planning, Media buying, Media optimisation, Data analysis, Stakeholder management, Agency management, Digital marketing, Brand marketing, ROI measurement, AI planning, Econometrics, Media modeling, Brand tracking, LinkedIn, Media owner relationships, Negotiation"},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_b5258a48-495"},"title":"Senior Data and Applied Scientist","description":"<p>Imagine shaping the future of local search for millions of users worldwide. At Bing Places, you&#39;ll join a team that powers business entity relevance on the search results page. You&#39;ll work on cutting-edge tools and metrics that ensure users find the most accurate and meaningful local results. Our team thrives on innovation, leveraging large and small language models, and advanced measurement systems to deliver exceptional quality.</p>\n<p>As a Data Scientist in Bing Places, you will design new relevance metrics, build labeling pipelines, and fine-tune language models to improve search quality. You&#39;ll work on prompt engineering, implement modern language models techniques like Retrieval Augmented Generation, and create scalable workflows for measurement and evaluation.</p>\n<p>This opportunity will allow you to:</p>\n<ul>\n<li>Accelerate your career growth by working on state-of-the-art AI systems.</li>\n<li>Develop deep expertise in prompt engineering and model tuning.</li>\n<li>Hone your skills in building robust data pipelines and quality frameworks.</li>\n</ul>\n<p>Microsoft&#39;s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.</p>\n<p>Responsibilities:</p>\n<ul>\n<li>Design and implement new relevance metrics to measure and improve local search quality.</li>\n<li>Develop and optimize LLM/SLM labeling pipelines for high-throughput, consistent quality judgments.</li>\n<li>Engineer and fine-tune prompts for LLMs to enhance query understanding and classification accuracy.</li>\n<li>Apply modern LLM techniques such as retrieval-augmented generation for improved grounding and relevance.</li>\n<li>Build scalable workflows and dashboards for measurement, evaluation cycles, and quality checks.</li>\n<li>Analyze failure modes and improve prompt rubrics to reduce defect rates and enhance labeling consistency.</li>\n<li>Collaborate with cross-functional teams to integrate metrics and labeling systems into production environments.</li>\n</ul>\n<p>Qualifications:</p>\n<ul>\n<li>Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND relevant data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) OR Master’s Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND relevant data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) OR Bachelor’s Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND relevant data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) OR equivalent experience.</li>\n<li>Relevant years customer-facing, project-delivery experience, professional services, and/or consulting experience.</li>\n</ul>\n<p>Other Requirements:</p>\n<ul>\n<li>Ability to meet Microsoft, customer and/or government security screening requirements are required for this role. These requirements include but are not limited to the following specialized security screenings: Microsoft Cloud Background Check: This position will be required to pass the Microsoft Cloud background check upon hire/transfer and every two years thereafter.</li>\n</ul>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_b5258a48-495","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Microsoft","sameAs":"https://microsoft.ai","logo":"https://logos.yubhub.co/microsoft.ai.png"},"x-apply-url":"https://microsoft.ai/job/senior-data-and-applied-scientist/","x-work-arrangement":"hybrid","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":null,"x-skills-required":["Data Science","Mathematics","Statistics","Econometrics","Economics","Operations Research","Computer Science","LLM/SLM labeling pipelines","Prompt engineering","Model tuning","Data pipelines","Quality frameworks"],"x-skills-preferred":[],"datePosted":"2026-03-08T22:19:32.251Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Barcelona"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, LLM/SLM labeling pipelines, Prompt engineering, Model tuning, Data pipelines, Quality frameworks"},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_87533f45-d48"},"title":"Data Scientist","description":"<p>The Bing organization is looking for a Data and Applied Scientist for its online metric team. The team is pushing the boundaries regarding online A/B experimentation capabilities and methods, as well as informs our understanding for how users engage with search engines and integrated AI experiences, and then translates the insights into actionable metrics. These metrics provide direction to the Bing and MAI organisation and help engineers make the right ship decisions for their thousands of online controlled experiments.</p>\n<p>Hundreds of millions of users visit Bing.com worldwide monthly, and we have a large opportunity to grow further. At Bing, we celebrate our data-driven culture: changes only ship when their impact is understood and positive. This role is a great opportunity to make solid, and even multiplicative impact on the org.</p>\n<p>As a data and applied scientist in this team, you will have the chance to work on and deliver metrics that drive the direction of major Bing initiatives. You will have the chance to be involved in the analysis and decision making for 1000s of online controlled A/B experiments.</p>\n<p>Microsoft’s mission is to empower every person and every organisation on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realise our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.</p>\n<p>Starting January 26, 2026, Microsoft AI (MAI) employees who live within a 50-mile commute of a designated Microsoft office in the U.S. or 25-mile commute of a non-U.S., country-specific location are expected to work from the office at least four days per week. This expectation is subject to local law and may vary by jurisdiction.</p>\n<p>Responsibilities:</p>\n<ul>\n<li>Design, analyse, and interpret A/B online experiments to evaluate user engagement and generate actionable, trustworthy insights that inform product decisions.</li>\n<li>Perform hands-on analysis of large-scale telemetry data using advanced statistical methods, algorithms, and data tools to uncover meaningful patterns and trends.</li>\n<li>Develop and monitor key success metrics to measure and improve Bing customer satisfaction, engagement, and retention.</li>\n<li>Formulate data-driven strategies to understand correlations among critical Bing metrics and deliver clear, rigorous ship decisions.</li>\n<li>Effectively communicate analytical methodologies, data visualisations, and evidence-based recommendations across cross-functional teams to drive alignment and impact.</li>\n</ul>\n<p>Qualifications:</p>\n<ul>\n<li>Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field OR Master’s Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 1+ year(s) data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) OR Bachelor’s Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 2+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) OR equivalent experience.</li>\n</ul>\n<p>Preferred Qualifications:</p>\n<ul>\n<li>Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 1+ year(s) data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) OR Master’s Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 3+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) OR Bachelor’s Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 5+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) OR equivalent experience.</li>\n</ul>\n<p>Experience with SQL-like query languages. Hands on experience in design &amp; problem-solving skills with one or more programming languages, such as Python, Java, C# or C++. Ability to work independently, influence others, and solid communication and collaboration skills. Familiarity with search engines, dealing with online instrumentation. Experience with large datasets and interest in consumer online search behaviours. Experience with building machine learning models on large scale data.</p>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_87533f45-d48","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Microsoft","sameAs":"https://microsoft.ai","logo":"https://logos.yubhub.co/microsoft.ai.png"},"x-apply-url":"https://microsoft.ai/job/data-scientist/","x-work-arrangement":"hybrid","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$100,600 – $199,000 per year","x-skills-required":["Data Science","Mathematics","Statistics","Econometrics","Economics","Operations Research","Computer Science","SQL-like query languages","Python","Java","C#","C++","Search engines","Online instrumentation","Large datasets","Machine learning models"],"x-skills-preferred":["Data Science","Mathematics","Statistics","Econometrics","Economics","Operations Research","Computer Science","SQL-like query languages","Python","Java","C#","C++","Search engines","Online instrumentation","Large datasets","Machine learning models"],"datePosted":"2026-03-08T22:19:25.553Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Redmond"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, SQL-like query languages, Python, Java, C#, C++, Search engines, Online instrumentation, Large datasets, Machine learning models, Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, SQL-like query languages, Python, Java, C#, C++, Search engines, Online instrumentation, Large datasets, Machine learning models","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":100600,"maxValue":199000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_4bd6468f-bc0"},"title":"Senior Applied Scientist","description":"<p>We&#39;re building the next-generation Grounding Service that powers the latest AI applications—chat assistants, copilots, and autonomous agents—with factual, cited, and trustworthy responses. Our platform stitches together retrieval, reasoning, and real-time data so that large language models stay anchored to enterprise knowledge, the public web, and proprietary tools.</p>\n<p>We&#39;re looking for a Senior Applied Scientist to lead end-to-end science for grounding: inventing retrieval and attribution methods, defining factuality/faithfulness metrics, and shipping production models and APIs that scale to billions of queries. You&#39;ll partner closely with engineering, product, research, and customers to deliver fast, reliable, and explainable answers with source citations across a diverse set of domains and modalities.</p>\n<p>As a team, we value curiosity, pragmatic rigor, and inclusive collaboration. We believe great systems emerge when scientists and engineers co-design metrics, models, and infrastructure—and when we obsess over customer impact, privacy, and safety.</p>\n<p>Responsibilities\n Owns the science roadmap for grounding—including retrieval, re-ranking, attribution, and reasoning—driving initiatives from problem framing to production impact.\n Designs and evolves state-of-the-art retrieval and RAG orchestration across documents, tables, code, and images.\n Builds citation and provenance systems (e.g., passage highlighting, quote-level alignment, confidence scoring) to reduce hallucinations and increase user trust.\n Leads experimentation and evaluation using A/B testing, interleaving, NDCG, MRR, precision/recall, and calibration curves to guide measurable trade-offs.\n Advances tool-augmented grounding through schema-aware retrieval, function calling, knowledge graph joins, and real-time connectors to databases, cloud object stores, search indexes, and the web.\n Partners with platform engineering to productionize models with scalable inference, embedding services, feature stores, caching, and privacy-compliant multi-tenant systems.\n Nurtures collaborative relationships with product and business leaders across Microsoft, influencing strategic decisions and driving business impact through technology.\n Authors white papers, contributes to internal tools and services, and may publish research to generate intellectual property.\n Bridges the gap between researchers (e.g., Microsoft Research) and development teams, applying long-term research to solve immediate product needs.\n Leads high-stakes negotiations to ensure cutting-edge technologies are applied practically and effectively.\n Identifies and solves significant business problems using novel, scalable, and data-driven solutions.\n Shapes the direction of Microsoft and the broader industry through pioneering product and tooling work.\n Mentors applied scientists and data scientists, establishing best practices in experimentation, error analysis, and incident review.\n Collaborates cross-functionally with PMs, research, infrastructure, and security teams to align on milestones, SLAs, and safety protocols.\n Communicates clearly through design documentation, progress updates, and presentations to executives and customers.\n Contributes to ethics and privacy policies, identifies bias in product development, and proposes mitigation strategies.</p>\n<p>Qualifications\n Required Qualifications:\n  Bachelor’s Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 4+ years related experience (e.g., statistics predictive analytics, research)\n  OR Master’s Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience (e.g., statistics, predictive analytics, research)\n  OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 1+ year(s) related experience (e.g., statistics, predictive analytics, research)\n  OR equivalent experience.\n  Minimum of 4 years of hands-on experience designing and building search, retrieval, or ranking systems.\n  Proven track record of shipping LLM-powered or Retrieval-Augmented Generation (RAG) systems into production environments.\n  Solid coding skills and solid foundation in machine learning, with the ability to implement and optimize models effectively.\n  Demonstrated ability to lead through ambiguity, make principled trade-offs, and deliver measurable impact in cross-functional, fast-paced settings.\n Preferred Qualifications:\n  Master’s Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 6+ years related experience (e.g., statistics, predictive analytics, research)\n  OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience (e.g., statistics, predictive analytics, research)\n  OR equivalent experience.\n  Demonstrated expertise in information retrieval, with publications in top-tier conferences or journals such as NeurIPS, ICML, ICLR, SIGIR, or ACL.\n  Hands-on experience in large language model (LLM) development, including pretraining, supervised fine-tuning (SFT), and reinforcement learning (RL).\n  Proven track record in optimizing LLM inference, or active contributions to open-source frameworks like vLLM, SGLang, or related projects.</p>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_4bd6468f-bc0","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Microsoft","sameAs":"https://microsoft.ai","logo":"https://logos.yubhub.co/microsoft.ai.png"},"x-apply-url":"https://microsoft.ai/job/senior-applied-scientist-38/","x-work-arrangement":"hybrid","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":null,"x-skills-required":["Statistics","Econometrics","Computer Science","Electrical or Computer Engineering","Search","Retrieval","Ranking","Machine Learning","Information Retrieval","Large Language Models","Pretraining","Supervised Fine-Tuning","Reinforcement Learning"],"x-skills-preferred":["Information Retrieval","Large Language Models","Pretraining","Supervised Fine-Tuning","Reinforcement Learning"],"datePosted":"2026-03-08T22:18:58.169Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Suzhou"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, Search, Retrieval, Ranking, Machine Learning, Information Retrieval, Large Language Models, Pretraining, Supervised Fine-Tuning, Reinforcement Learning, Information Retrieval, Large Language Models, Pretraining, Supervised Fine-Tuning, Reinforcement Learning"},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_d0214534-b6a"},"title":"Senior Applied Scientist","description":"<p>We&#39;re building the next-generation Grounding Service that powers the latest AI applications—chat assistants, copilots, and autonomous agents—with factual, cited, and trustworthy responses. Our platform stitches together retrieval, reasoning, and real-time data so that large language models stay anchored to enterprise knowledge, the public web, and proprietary tools. We&#39;re looking for a Senior Applied Scientist to lead end-to-end science for grounding: inventing retrieval and attribution methods, defining factuality/faithfulness metrics, and shipping production models and APIs that scale to billions of queries. You&#39;ll partner closely with engineering, product, research, and customers to deliver fast, reliable, and explainable answers with source citations across a diverse set of domains and modalities. As a team, we value curiosity, pragmatic rigor, and inclusive collaboration. We believe great systems emerge when scientists and engineers co-design metrics, models, and infrastructure—and when we obsess over customer impact, privacy, and safety. Microsoft&#39;s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond. Starting January 26, 2026, Microsoft AI (MAI) employees who live within a 50-mile commute of a designated Microsoft office in the U.S. or 25-mile commute of a non-U.S., country-specific location are expected to work from the office at least four days per week. This expectation is subject to local law and may vary by jurisdiction. Responsibilities</p>\n<p>Owns the science roadmap for grounding—including retrieval, re-ranking, attribution, and reasoning—driving initiatives from problem framing to production impact. Designs and evolves state-of-the-art retrieval and RAG orchestration across documents, tables, code, and images. Builds citation and provenance systems (e.g., passage highlighting, quote-level alignment, confidence scoring) to reduce hallucinations and increase user trust. Leads experimentation and evaluation using A/B testing, interleaving, NDCG, MRR, precision/recall, and calibration curves to guide measurable trade-offs. Advances tool-augmented grounding through schema-aware retrieval, function calling, knowledge graph joins, and real-time connectors to databases, cloud object stores, search indexes, and the web. Partners with platform engineering to productionize models with scalable inference, embedding services, feature stores, caching, and privacy-compliant multi-tenant systems. Nurtures collaborative relationships with product and business leaders across Microsoft, influencing strategic decisions and driving business impact through technology. Authors white papers, contributes to internal tools and services, and may publish research to generate intellectual property. Bridges the gap between researchers (e.g., Microsoft Research) and development teams, applying long-term research to solve immediate product needs. Leads high-stakes negotiations to ensure cutting-edge technologies are applied practically and effectively. Identifies and solves significant business problems using novel, scalable, and data-driven solutions. Shapes the direction of Microsoft and the broader industry through pioneering product and tooling work. Mentors applied scientists and data scientists, establishing best practices in experimentation, error analysis, and incident review. Collaborates cross-functionally with PMs, research, infrastructure, and security teams to align on milestones, SLAs, and safety protocols. Communicates clearly through design documentation, progress updates, and presentations to executives and customers. Contributes to ethics and privacy policies, identifies bias in product development, and proposes mitigation strategies.</p>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_d0214534-b6a","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Microsoft","sameAs":"https://microsoft.ai","logo":"https://logos.yubhub.co/microsoft.ai.png"},"x-apply-url":"https://microsoft.ai/job/senior-applied-scientist-37/","x-work-arrangement":"hybrid","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":null,"x-skills-required":["Statistics","Econometrics","Computer Science","Electrical or Computer Engineering","Machine Learning","Information Retrieval","Large Language Model Development","Pretraining","Supervised Fine-Tuning","Reinforcement Learning","Optimizing LLM Inference"],"x-skills-preferred":["Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field","6+ years related experience (e.g., statistics, predictive analytics, research)","Demonstrated expertise in information retrieval, with publications in top-tier conferences or journals such as NeurIPS, ICML, ICLR, SIGIR, or ACL","Hands-on experience in large language model (LLM) development, including pretraining, supervised fine-tuning (SFT), and reinforcement learning (RL)","Proven track record in optimizing LLM inference, or active contributions to open-source frameworks like vLLM, SGLang, or related projects"],"datePosted":"2026-03-08T22:16:41.766Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Beijing"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, Machine Learning, Information Retrieval, Large Language Model Development, Pretraining, Supervised Fine-Tuning, Reinforcement Learning, Optimizing LLM Inference, Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field, 6+ years related experience (e.g., statistics, predictive analytics, research), Demonstrated expertise in information retrieval, with publications in top-tier conferences or journals such as NeurIPS, ICML, ICLR, SIGIR, or ACL, Hands-on experience in large language model (LLM) development, including pretraining, supervised fine-tuning (SFT), and reinforcement learning (RL), Proven track record in optimizing LLM inference, or active contributions to open-source frameworks like vLLM, SGLang, or related projects"},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_714d4a02-1c4"},"title":"Applied Scientist","description":"<p>Imagine shaping the future of local search for millions of users worldwide. At Bing Places, you&#39;ll join a team that powers business entity relevance on the search results page. You&#39;ll work on cutting-edge tools and metrics that ensure users find the most accurate and meaningful local results. Our team thrives on innovation, leveraging large and small language models, and advanced measurement systems to deliver exceptional quality.</p>\n<p>As a Applied Scientist in Bing Places, you will design new relevance metrics, build labeling pipelines, and fine-tune language models to improve search quality. You&#39;ll work on prompt engineering, implement modern language models techniques like Retrieval Augmented Generation, and create scalable workflows for measurement and evaluation.</p>\n<p>This opportunity will allow you to:</p>\n<ul>\n<li>Accelerate your career growth by working on state-of-the-art AI systems.</li>\n<li>Develop deep expertise in prompt engineering and model tuning.</li>\n<li>Hone your skills in building robust data pipelines and quality frameworks.</li>\n</ul>\n<p>Microsoft&#39;s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.</p>\n<p>Responsibilities:</p>\n<ul>\n<li>Design and implement new relevance metrics to measure and improve local search quality.</li>\n<li>Develop and optimize LLM/SLM labeling pipelines for high-throughput, consistent quality judgments.</li>\n<li>Engineer and fine-tune prompts for LLMs to enhance query understanding and classification accuracy.</li>\n<li>Apply modern LLM techniques such as retrieval-augmented generation for improved grounding and relevance.</li>\n<li>Build scalable workflows and dashboards for measurement, evaluation cycles, and quality checks.</li>\n<li>Analyze failure modes and improve prompt rubrics to reduce defect rates and enhance labeling consistency.</li>\n<li>Collaborate with cross-functional teams to integrate metrics and labeling systems into production environments.</li>\n</ul>\n<p>Qualifications:</p>\n<ul>\n<li>Bachelor’s Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND hands on experience (e.g., statistics, predictive analytics, research) OR Master’s Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND hands on experience (e.g., statistics, predictive analytics, research) OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field OR equivalent experience.</li>\n</ul>\n<p>Other Requirements:</p>\n<ul>\n<li>Ability to meet Microsoft, customer and/or government security screening requirements are required for this role. These requirements include but are not limited to the following specialized security screenings: Microsoft Cloud Background Check: This position will be required to pass the Microsoft Cloud background check upon hire/transfer and every two years thereafter.</li>\n</ul>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_714d4a02-1c4","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Microsoft","sameAs":"https://microsoft.ai","logo":"https://logos.yubhub.co/microsoft.ai.png"},"x-apply-url":"https://microsoft.ai/job/applied-scientist-7/","x-work-arrangement":"hybrid","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":null,"x-skills-required":["Statistics","Econometrics","Computer Science","Electrical or Computer Engineering","LLM/SLM labeling pipelines","Prompt engineering","Model tuning","Data pipelines","Quality frameworks"],"x-skills-preferred":["Retrieval Augmented Generation","Scalable workflows","Dashboards","Measurement","Evaluation cycles","Quality checks"],"datePosted":"2026-03-08T22:15:35.607Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Barcelona"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, LLM/SLM labeling pipelines, Prompt engineering, Model tuning, Data pipelines, Quality frameworks, Retrieval Augmented Generation, Scalable workflows, Dashboards, Measurement, Evaluation cycles, Quality checks"},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_b2f91c0a-0b3"},"title":"Principal Applied Scientist","description":"<p>We are seeking a Principal Applied Scientist to lead the next generation of click-through-rate (CTR) for Microsoft Advertising. This is a high-impact role responsible for advancing large-scale ranking models that power Microsoft Advertising, generating billions of impressions and revenue-critical decisions daily. You will combine deep machine learning expertise, solid engineering execution, and business intuition to modernize our prediction stack, drive model innovation, and mentor a growing team of scientists and engineers. This role is ideal for someone who thrives in complex, high-scale systems, who brings thought leadership to ML strategy, and who raises the bar for engineering rigor, curiosity, and business-driven decision making across the team.</p>\n<p>Responsibilities:</p>\n<ul>\n<li>Lead the end-to-end development of large-scale CTR and other user response signal models for Search and Display ads.</li>\n<li>Design, prototype, and ship cutting-edge ML architectures (deep models, multi-task, transformer-based, LLM-assisted, multimodal).</li>\n<li>Define long-term modeling strategy and roadmap with clear business impact.</li>\n</ul>\n<p>Technical &amp; Engineering Execution:</p>\n<ul>\n<li>Modernize our current modeling pipelines, addressing critical technical debt in data flows, training pipelines, and inference systems.</li>\n<li>Partner closely with engineering teams to improve reliability, monitoring, and performance of distributed training and online serving.</li>\n<li>Introduce best practices for experiment design, ablations, feature validation, and productionization.</li>\n</ul>\n<p>Business &amp; Product Impact:</p>\n<ul>\n<li>Work with PMs, monetization teams, and auction experts to translate business needs into modeling goals.</li>\n<li>Own model performance holistically: quality, stability, latency, and revenue impact.</li>\n<li>Develop frameworks to better understand advertiser value, user behavior, and marketplace dynamics.</li>\n</ul>\n<p>Leadership &amp; Mentorship:</p>\n<ul>\n<li>Mentor and up-level applied scientists and ML engineers across the organization.</li>\n<li>Drive a culture of curiosity, deep system understanding, and high-quality scientific reasoning.</li>\n<li>Improve collaboration norms, documentation quality, and cross-team alignment.</li>\n</ul>\n<p>Innovation &amp; Tooling:</p>\n<ul>\n<li>Leverage and influence LLM-based tooling (e.g., agents, copilots) to improve team productivity and model development velocity.</li>\n<li>Identify opportunities to incorporate new modeling signals, architectures, or evaluation metrics.</li>\n</ul>\n<p>Qualifications:</p>\n<ul>\n<li>Bachelor’s Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 6+ years related experience (e.g., statistics, predictive analytics, research) OR Master’s Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 4+ years related experience (e.g., statistics, predictive analytics, research) OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience (e.g., statistics, predictive analytics, research) OR equivalent experience.</li>\n</ul>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_b2f91c0a-0b3","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Microsoft","sameAs":"https://microsoft.ai","logo":"https://logos.yubhub.co/microsoft.ai.png"},"x-apply-url":"https://microsoft.ai/job/principal-applied-scientist-10/","x-work-arrangement":"hybrid","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$139,900 – $274,800 per year","x-skills-required":["Machine Learning","Deep Learning","Statistics","Econometrics","Computer Science","Electrical or Computer Engineering"],"x-skills-preferred":["LLM-based tooling","Experiment design","Ablations","Feature validation","Productionization"],"datePosted":"2026-03-08T22:15:19.795Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Redmond"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Machine Learning, Deep Learning, Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, LLM-based tooling, Experiment design, Ablations, Feature validation, Productionization","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":139900,"maxValue":274800,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_14fdcb43-401"},"title":"Data Scientist, Strategic Intelligence & Risk","description":"<p><strong>Data Scientist, Strategic Intelligence &amp; Risk</strong></p>\n<p><strong>Location</strong></p>\n<p>San Francisco</p>\n<p><strong>Employment Type</strong></p>\n<p>Full time</p>\n<p><strong>Department</strong></p>\n<p>Intelligence &amp; Investigations</p>\n<p><strong>Compensation</strong></p>\n<ul>\n<li>$230K – $325K • Offers Equity</li>\n</ul>\n<p>The base pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. If the role is non-exempt, overtime pay will be provided consistent with applicable laws. In addition to the salary range listed above, total compensation also includes generous equity, performance-related bonus(es) for eligible employees, and the following benefits.</p>\n<p><strong>Benefits</strong></p>\n<ul>\n<li>Medical, dental, and vision insurance for you and your family, with employer contributions to Health Savings Accounts</li>\n</ul>\n<ul>\n<li>Pre-tax accounts for Health FSA, Dependent Care FSA, and commuter expenses (parking and transit)</li>\n</ul>\n<ul>\n<li>401(k) retirement plan with employer match</li>\n</ul>\n<ul>\n<li>Paid parental leave (up to 24 weeks for birth parents and 20 weeks for non-birthing parents), plus paid medical and caregiver leave (up to 8 weeks)</li>\n</ul>\n<ul>\n<li>Paid time off: flexible PTO for exempt employees and up to 15 days annually for non-exempt employees</li>\n</ul>\n<ul>\n<li>13+ paid company holidays, and multiple paid coordinated company office closures throughout the year for focus and recharge, plus paid sick or safe time (1 hour per 30 hours worked, or more, as required by applicable state or local law)</li>\n</ul>\n<ul>\n<li>Mental health and wellness support</li>\n</ul>\n<ul>\n<li>Employer-paid basic life and disability coverage</li>\n</ul>\n<ul>\n<li>Annual learning and development stipend to fuel your professional growth</li>\n</ul>\n<ul>\n<li>Daily meals in our offices, and meal delivery credits as eligible</li>\n</ul>\n<ul>\n<li>Relocation support for eligible employees</li>\n</ul>\n<ul>\n<li>Additional taxable fringe benefits, such as charitable donation matching and wellness stipends, may also be provided.</li>\n</ul>\n<p><strong>About the Team</strong></p>\n<p>The Intelligence and Investigations team seeks to rapidly identify and mitigate abuse and strategic risks to ensure a safe online ecosystem. We are dedicated to identifying emerging abuse trends, analyzing risks, and working with our internal and external partners to implement effective mitigation strategies to protect against misuse. Our efforts contribute to OpenAI&#39;s overarching goal of developing AI that benefits humanity.</p>\n<p><strong>About the Role</strong></p>\n<p>As a Data Scientist, you will lead econometric and experimental analysis to understand how risk changes in complex human–AI systems. Your work will focus on measuring the magnitude and impact of risk shifts in a fast-paced, rapidly evolving operational environment. You will design experiments and observational studies to identify causal drivers and analyze changes in risk across a wide range of surfaces and sources. Your analyses will directly inform prioritization and strategic risk management across the company.</p>\n<p><strong>In this role, you will:</strong></p>\n<ul>\n<li>Own the design and execution of experimental and observational analyses used to assess strategic risk</li>\n</ul>\n<ul>\n<li>Develop econometric approaches to estimate the impact of product, policy, and external developments on key risk vectors</li>\n</ul>\n<ul>\n<li>Translate strategic risk questions into testable hypotheses and sound study designs</li>\n</ul>\n<ul>\n<li>Design and deploy A/B tests, as well as pseudo-experimental studies, to measure changes in risks and understand underlying mechanisms</li>\n</ul>\n<ul>\n<li>Identify, test, and explain product-driven, event-driven, or signal-driven changes in risk</li>\n</ul>\n<ul>\n<li>Establish baselines and statistical confidence around core metrics to size these problems</li>\n</ul>\n<ul>\n<li>Partner across teams to track strategic risks, identify opportunities for intervention, and develop analyses to evaluate those interventions</li>\n</ul>\n<p><strong>You might thrive in this role if you:</strong></p>\n<ul>\n<li>Have 3–6+ years in econometrics, causal inference, or experimental research</li>\n</ul>\n<ul>\n<li>Are comfortable owning ambiguous analyses with large-scale influence</li>\n</ul>\n<ul>\n<li>Are strong in experimental design, observational methods, and statistical reasoning</li>\n</ul>\n<ul>\n<li>Write solid Python and SQL</li>\n</ul>\n<ul>\n<li>Experience delivering zero-to-one analyses and scaling them from concept through deployment</li>\n</ul>\n<ul>\n<li>Communicate data-driven findings clearly, including uncertainty and trade-offs, to non-technical partners and leadership</li>\n</ul>\n<ul>\n<li>Nice to have: experience in trust and safety, integrity, operational security, intelligence analysis or other quantitative risk-focused domains</li>\n</ul>\n<p><strong>About OpenAI</strong></p>\n<p>OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity.</p>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_14fdcb43-401","directApply":true,"hiringOrganization":{"@type":"Organization","name":"OpenAI","sameAs":"https://jobs.ashbyhq.com","logo":"https://logos.yubhub.co/openai.com.png"},"x-apply-url":"https://jobs.ashbyhq.com/openai/6131fc4f-bfc8-49f3-8223-773a55d15583","x-work-arrangement":"hybrid","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$230K – $325K • Offers Equity","x-skills-required":["econometrics","causal inference","experimental research","Python","SQL","experimental design","observational methods","statistical reasoning"],"x-skills-preferred":["trust and safety","integrity","operational security","intelligence analysis"],"datePosted":"2026-03-06T18:34:25.237Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"econometrics, causal inference, experimental research, Python, SQL, experimental design, observational methods, statistical reasoning, trust and safety, integrity, operational security, intelligence analysis","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":230000,"maxValue":325000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_d8710a49-05d"},"title":"Principal Applied Scientist","description":"<p><strong>Summary</strong></p>\n<p>Microsoft AI are looking for a talented Principal Applied Scientist at their New York office. This role sits at the heart of advanced AI at web scale, shaping the future of key systems within Microsoft Ads, Copilot, and beyond. You&#39;ll work directly with leadership to deliver scalable solutions that enhance ad relevance and optimize user and advertiser experiences.</p>\n<p><strong>About the Role</strong></p>\n<p>In this role, the Principal Applied Scientist will design and implement state-of-the-art machine learning models and algorithms that power key systems within Microsoft Ads, Copilot, and beyond. The work will directly impact millions of users and advertisers by delivering scalable solutions that enhance ad relevance and optimize user and advertiser experiences.</p>\n<p><strong>Accountabilities</strong></p>\n<ul>\n<li>Develop and deploy cutting-edge machine learning models, including transformers, generative AI, and reinforcement learning, to optimize user interactions and ad relevance across Microsoft Ads and Copilot.</li>\n<li>Design scalable algorithms for online and offline systems, delivering innovative solutions for ads selection, ad generation and ad relevance.</li>\n</ul>\n<p><strong>The Candidate we&#39;re looking for</strong></p>\n<p><strong>Experience:</strong></p>\n<ul>\n<li>Bachelor’s Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 6+ years related experience (e.g., statistics, predictive analytics, research) OR Master’s Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 4+ years related experience (e.g., statistics, predictive analytics, research) OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience (e.g., statistics, predictive analytics, research) OR equivalent experience.</li>\n</ul>\n<p><strong>Technical skills:</strong></p>\n<ul>\n<li>Proven experience in programming and data analysis skills.</li>\n<li>Proven expertise in the areas of Generative AI, deep learning, Reinforcement learning, transformers or LLM.</li>\n</ul>\n<p><strong>Personal attributes:</strong></p>\n<ul>\n<li>6+ years of experience in developing and deploying large-scale machine learning models.</li>\n</ul>\n<p><strong>Benefits</strong></p>\n<ul>\n<li>Competitive salary</li>\n<li>Comprehensive benefits package</li>\n<li>Opportunities for professional growth and development</li>\n<li>Collaborative and dynamic work environment</li>\n</ul>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_d8710a49-05d","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Microsoft AI","sameAs":"https://microsoft.ai","logo":"https://logos.yubhub.co/microsoft.ai.png"},"x-apply-url":"https://microsoft.ai/job/principal-applied-scientist-17/","x-work-arrangement":"hybrid","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$139,900 – $274,800 per year","x-skills-required":["machine learning","statistics","econometrics","computer science","electrical or computer engineering"],"x-skills-preferred":["generative AI","deep learning","reinforcement learning","transformers","LLM"],"datePosted":"2026-03-06T07:33:03.226Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"New York"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"machine learning, statistics, econometrics, computer science, electrical or computer engineering, generative AI, deep learning, reinforcement learning, transformers, LLM","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":139900,"maxValue":274800,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_066d45bf-f6e"},"title":"Principal Applied Scientist","description":"<p><strong>Summary</strong></p>\n<p>Microsoft AI are looking for a talented Principal Applied Scientist at their Mountain View office. This role sits at the heart of advanced AI at web scale, shaping the future of key systems within Microsoft Ads, Copilot, and beyond. You&#39;ll work directly with leadership to deliver scalable solutions that enhance ad relevance and optimize user and advertiser experiences.</p>\n<p><strong>About the Role</strong></p>\n<p>In this role, the Principal Applied Scientist will design and implement state-of-the-art machine learning models and algorithms that power key systems within Microsoft Ads, Copilot, and beyond. The work will directly impact millions of users and advertisers by delivering scalable solutions that enhance ad relevance and optimize user and advertiser experiences.</p>\n<p><strong>Accountabilities</strong></p>\n<ul>\n<li>Develop and deploy cutting-edge machine learning models, including transformers, generative AI, and reinforcement learning, to optimize user interactions and ad relevance across Microsoft Ads and Copilot.</li>\n<li>Design scalable algorithms for online and offline systems, delivering innovative solutions for ads selection, ad generation and ad relevance.</li>\n</ul>\n<p><strong>The Candidate we&#39;re looking for</strong></p>\n<p><strong>Experience:</strong></p>\n<ul>\n<li>Bachelor’s Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 6+ years related experience (e.g., statistics, predictive analytics, research) OR Master’s Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 4+ years related experience (e.g., statistics, predictive analytics, research) OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience (e.g., statistics, predictive analytics, research) OR equivalent experience.</li>\n</ul>\n<p><strong>Technical skills:</strong></p>\n<ul>\n<li>Proven experience in programming and data analysis skills.</li>\n<li>Proven expertise in the areas of Generative AI, deep learning, Reinforcement learning, transformers or LLM.</li>\n</ul>\n<p><strong>Personal attributes:</strong></p>\n<ul>\n<li>Proven experience in developing and deploying large-scale machine learning models.</li>\n</ul>\n<p><strong>Benefits</strong></p>\n<ul>\n<li>Competitive salary</li>\n<li>Comprehensive benefits package</li>\n<li>Opportunities for professional growth and development</li>\n<li>Collaborative and dynamic work environment</li>\n</ul>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_066d45bf-f6e","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Microsoft AI","sameAs":"https://microsoft.ai","logo":"https://logos.yubhub.co/microsoft.ai.png"},"x-apply-url":"https://microsoft.ai/job/principal-applied-scientist-16/","x-work-arrangement":"onsite","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$139,900 – $274,800 per year","x-skills-required":["machine learning","statistics","econometrics","computer science","electrical or computer engineering"],"x-skills-preferred":["generative AI","deep learning","reinforcement learning","transformers","LLM"],"datePosted":"2026-03-06T07:32:49.983Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Mountain View"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"machine learning, statistics, econometrics, computer science, electrical or computer engineering, generative AI, deep learning, reinforcement learning, transformers, LLM","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":139900,"maxValue":274800,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_142c12c6-555"},"title":"Principal Applied Scientist","description":"<p><strong>Summary</strong></p>\n<p>Microsoft AI are looking for a talented Principal Applied Scientist at their Redmond office. This role sits at the heart of scientific and technical strategy for data-driven attribution and causal measurement across advertising systems. You will help define the future of data-driven attribution and causal measurement, shaping the methodologies that determine how value is estimated and optimized across the ecosystem.</p>\n<p><strong>About the Role</strong></p>\n<p>As a Principal Applied Scientist, you will help define the scientific and technical strategy for data-driven attribution (DDA) and causal measurement across advertising systems. You will establish methodologies for incrementality estimation, counterfactual learning, delayed-feedback modeling, and bias correction in environments with partial observability. You will lead the design and production adoption of attribution and causal inference frameworks that improve bidding, ranking, optimization, and advertiser ROI at web scale. You will set evaluation standards that distinguish correlation from causation and elevate experimental rigor across teams. You will identify capability gaps and introduce advanced research, tools, or modeling approaches to strengthen measurement foundations. 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This role sits at the heart of advanced AI at web scale, shaping the future of key systems within Microsoft Ads, Copilot, and beyond. You&#39;ll design and implement state-of-the-art machine learning models and algorithms that power scalable solutions that enhance ad relevance and optimize user and advertiser experiences.</p>\n<p><strong>About the Role</strong></p>\n<p>In this role, you will develop and deploy cutting-edge machine learning models, including transformers, generative AI, and reinforcement learning, to optimize user interactions and ad relevance across Microsoft Ads and Copilot. You will design scalable algorithms for online and offline systems, delivering innovative solutions for ads selection, ad generation, and ad relevance. You will drive experimentation through A/B testing and offline validation to evaluate model performance and refine user behavior predictions. 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This role sits at the heart of strategic decision-making, turning market data into actionable insights for a company that&#39;s revolutionising AI-powered web search. You&#39;ll work directly with leadership to shape the company&#39;s direction in the online experimentation and AI experiences markets.</p>\n<p><strong>About the Role</strong></p>\n<p>The Bing organization is looking for a Principal Data and Applied Scientist for its online metric team. The team is pushing the boundaries of online A/B experimentation capabilities and impact measurement methods, as well as informs our understanding for how users engage with search engines and integrated AI experiences and then translates the insights into actionable metrics. These metrics provide direction to the Bing and MAI organization and help engineers make the right ship decisions for their thousands of A/B experiments. Bing.com reaches about a billion people worldwide, and we have a large opportunity to grow further. At Bing, we celebrate our data-driven culture: changes only ship when their impact is understood and positive. This role is at the center of what defines our decision-making processes and is an excellent opportunity to make a multiplicative impact across the org.</p>\n<p><strong>Accountabilities</strong></p>\n<ul>\n<li>Drive innovation in large-scale online A/B experimentation for AI-powered web search, designing, building, and monitoring success metrics that directly measure user satisfaction, trust, and long-term retention across Bing experiences.</li>\n<li>Serve as a technical visionary and thought leader in online experimentation, shaping the future of product learning through research-driven, AI-enabled approaches that support trustworthy, agile, and evidence-based decision-making at global scale.</li>\n</ul>\n<p><strong>The Candidate we&#39;re looking for</strong></p>\n<p><strong>Experience:</strong></p>\n<ul>\n<li>Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 5+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) OR Master’s Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 7+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) OR Bachelor’s Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 10+ years data science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) OR equivalent experience.</li>\n</ul>\n<p><strong>Technical skills:</strong></p>\n<ul>\n<li>Experience with SQL-like query languages</li>\n<li>Hands on experience in design &amp; problem-solving skills with one or more programming languages, such as Python, Java, C# or C++</li>\n</ul>\n<p><strong>Personal attributes:</strong></p>\n<ul>\n<li>Ability to work independently, influence others, and solid communication and collaboration skills.</li>\n</ul>\n<p><strong>Benefits</strong></p>\n<ul>\n<li>Competitive salary</li>\n<li>Comprehensive benefits package</li>\n<li>Opportunities for professional growth and development</li>\n<li>Collaborative and dynamic work environment</li>\n<li>Recognition and rewards for outstanding performance</li>\n</ul>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_22f56698-eb9","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Microsoft AI","sameAs":"https://microsoft.ai","logo":"https://logos.yubhub.co/microsoft.ai.png"},"x-apply-url":"https://microsoft.ai/job/principal-data-scientist-10/","x-work-arrangement":"onsite","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"Competitive salary","x-skills-required":["Data Science","Mathematics","Statistics","Econometrics","Economics","Operations Research","Computer Science"],"x-skills-preferred":["SQL-like query languages","Python","Java","C#","C++"],"datePosted":"2026-03-06T07:28:08.193Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Redmond"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, SQL-like query languages, Python, Java, C#, C++"},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_ff5ec894-29f"},"title":"Principal Applied Scientist","description":"<p><strong>Summary</strong></p>\n<p>Microsoft are looking for a talented Principal Applied Scientist at their Mountain View office. This role sits at the heart of advancing large-scale ranking models that power Microsoft Advertising, generating billions of impressions and revenue-critical decisions daily. You will combine deep machine learning expertise, solid engineering execution, and business intuition to modernize our prediction stack, drive model innovation, and mentor a growing team of scientists and engineers.</p>\n<p><strong>About the Role</strong></p>\n<p>We are seeking a Principal Applied Scientist to lead the next generation of click-through-rate (CTR) for Microsoft Advertising. This is a high-impact role responsible for advancing large-scale ranking models that power Microsoft Advertising, generating billions of impressions and revenue-critical decisions daily. You will combine deep machine learning expertise, solid engineering execution, and business intuition to modernize our prediction stack, drive model innovation, and mentor a growing team of scientists and engineers. This role is ideal for someone who thrives in complex, high-scale systems, who brings thought leadership to ML strategy, and who raises the bar for engineering rigor, curiosity, and business-driven decision making across the team.</p>\n<p><strong>Accountabilities</strong></p>\n<ul>\n<li>Lead the end-to-end development of large-scale CTR and other user response signal models for Search and Display ads.</li>\n<li>Design, prototype, and ship cutting-edge ML architectures (deep models, multi-task, transformer-based, LLM-assisted, multimodal).</li>\n</ul>\n<p><strong>The Candidate we&#39;re looking for</strong></p>\n<p><strong>Experience:</strong></p>\n<ul>\n<li>Bachelor’s Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 6+ years related experience (e.g., statistics, predictive analytics, research) OR Master’s Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 4+ years related experience (e.g., statistics, predictive analytics, research) OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience (e.g., statistics, predictive analytics, research) OR equivalent experience.</li>\n</ul>\n<p><strong>Technical skills:</strong></p>\n<ul>\n<li>5+ years experience creating publications (e.g., patents, libraries, peer-reviewed academic papers).</li>\n<li>2+ years experience presenting at conferences or other events in the outside research/industry community as an invited speaker.</li>\n<li>5+ years experience conducting research as part of a research program (in academic or industry settings).</li>\n</ul>\n<p><strong>Personal attributes:</strong></p>\n<ul>\n<li>3+ years experience developing and deploying live production systems, as part of a product team.</li>\n<li>3+ years experience developing and deploying products or systems at multiple points in the product cycle from ideation to shipping.</li>\n</ul>\n<p><strong>Benefits</strong></p>\n<ul>\n<li>Competitive salary.</li>\n<li>Comprehensive benefits package.</li>\n<li>Opportunities for professional growth and development.</li>\n<li>Collaborative and dynamic work environment.</li>\n</ul>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_ff5ec894-29f","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Microsoft","sameAs":"https://microsoft.ai","logo":"https://logos.yubhub.co/microsoft.ai.png"},"x-apply-url":"https://microsoft.ai/job/principal-applied-scientist-11/","x-work-arrangement":"onsite","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$139,900 - $274,800 per year","x-skills-required":["Machine Learning","Statistics","Econometrics","Computer Science","Electrical or Computer Engineering"],"x-skills-preferred":["Deep Learning","Natural Language Processing","Computer Vision"],"datePosted":"2026-03-06T07:27:54.895Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Mountain View"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Machine Learning, Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, Deep Learning, Natural Language Processing, Computer Vision","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":139900,"maxValue":274800,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_8672228f-4df"},"title":"Principal Applied Scientist","description":"<p><strong>Summary</strong></p>\n<p>Microsoft AI are looking for a talented Principal Applied Scientist at their Sunnyvale office. This role sits at the heart of strategic decision-making, turning market data into actionable insights for a company that&#39;s revolutionising the advertising marketplace. You&#39;ll work directly with leadership to shape the company&#39;s direction in the development of large-scale learning systems that infer intent and causal effects from incomplete and noisy feedback.</p>\n<p><strong>About the Role</strong></p>\n<p>Our Signals Modeling team builds the intelligence that powers how the advertising marketplace understands user behavior, measures impact and optimizes outcomes from initial impressions through downstream conversions and long-term advertiser value. We develop large-scale learning systems that infer intent and causal effects from incomplete and noisy feedback, enabling principled decision-making across ranking, bidding, pricing, and budget allocation. Our work sits at the foundation of marketplace optimization, where accurate attribution and measurement directly influence billions in advertising spend. The team designs and operates state-of-the-art modeling platforms spanning representation learning, weak-supervision, multi-objective training, calibration, and rigorous experimentation. We transform sparse engagement signals into reliable learning targets and build models that remain robust under delayed conversions, selection bias, and rapidly shifting marketplace dynamics.</p>\n<p><strong>Accountabilities</strong></p>\n<ul>\n<li>Define and drive the scientific and technical strategy for data-driven attribution (DDA) and causal measurement across advertising systems.</li>\n<li>Establish methodologies for incrementality estimation, counterfactual learning, delayed-feedback modeling, and bias correction in environments with partial observability.</li>\n</ul>\n<p><strong>The Candidate we&#39;re looking for</strong></p>\n<p><strong>Experience:</strong></p>\n<ul>\n<li>Bachelor’s Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 6+ years related experience (e.g., statistics, predictive analytics, research) OR Master’s Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 4+ years related experience (e.g., statistics, predictive analytics, research) OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience (e.g., statistics, predictive analytics, research) OR equivalent experience.</li>\n</ul>\n<p><strong>Technical skills:</strong></p>\n<ul>\n<li>Recognized expertise in attribution, incrementality, marketplace experimentation, or causal ML.</li>\n</ul>\n<p><strong>Personal attributes:</strong></p>\n<ul>\n<li>Track record of driving multi-year research or modeling agendas that materially improved product outcomes.</li>\n</ul>\n<p><strong>Benefits</strong></p>\n<ul>\n<li>Competitive salary and benefits package.</li>\n<li>Opportunities for professional growth and development.</li>\n<li>Collaborative and dynamic work environment.</li>\n</ul>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_8672228f-4df","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Microsoft AI","sameAs":"https://microsoft.ai","logo":"https://logos.yubhub.co/microsoft.ai.png"},"x-apply-url":"https://microsoft.ai/job/principal-applied-scientist-19/","x-work-arrangement":"onsite","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"Competitive salary and benefits package.","x-skills-required":["Statistics","Econometrics","Computer Science","Electrical or Computer Engineering","Machine Learning","Data Science","Predictive Analytics","Research"],"x-skills-preferred":["Attribution","Incrementality","Marketplace Experimentation","Causal ML"],"datePosted":"2026-03-06T07:27:51.396Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Sunnyvale"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, Machine Learning, Data Science, Predictive Analytics, Research, Attribution, Incrementality, Marketplace Experimentation, Causal ML"},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_d446c7ab-5f0"},"title":"Member of Technical Staff, Applied Scientist - Windows Copilot","description":"<p><strong>Summary</strong></p>\n<p>Microsoft are looking for a talented Member of Technical Staff, Applied Scientist - Windows Copilot at their Redmond office. This role sits at the heart of redefining how AI enhances everyday computing. You&#39;ll work directly with leadership to shape the company&#39;s direction in the Windows Copilot team.</p>\n<p><strong>About the Role</strong></p>\n<p>The Windows Copilot team is at the forefront of redefining how AI enhances everyday computing. This team owns the full stack—from cutting-edge AI infrastructure and model development, to crafting seamless user experiences directly in Windows. We’re building and shipping consumer-scale services that are transforming how users interact with their PCs. Whether it’s designing intelligent prompts, engineering robust backends to interface with models, or developing native Windows platform and UX features, this team does it all.</p>\n<p>As an Applied Scientist, you will lead the end-to-end model-building process, including problem understanding, data curation, model development, deployment, and iteration based on real-world feedback. This role will serve as a critical bridge between Microsoft Research and the engineering team, taking increasing ownership of model training responsibilities.</p>\n<p><strong>Accountabilities</strong></p>\n<ul>\n<li>Develop and refine data pipelines and infrastructure to support AI model development for Copilot.</li>\n<li>Collaborate with research teams to integrate cutting-edge AI advancements into production systems.</li>\n<li>Design, train, and evaluate machine learning models, ensuring performance optimization and scalability.</li>\n<li>Work closely with engineering and product teams to ensure AI-driven experiences meet quality and user experience standards.</li>\n<li>Conduct rigorous data analysis and experimentation, leveraging insights to improve Copilot’s intelligence.</li>\n<li>Overcome obstacles to deliver iterative improvements in AI performance and responsiveness.</li>\n<li>Stay ahead of the latest innovations in deep learning, reinforcement learning, and generative AI.</li>\n</ul>\n<p><strong>The Candidate we&#39;re looking for</strong></p>\n<p><strong>Experience:</strong></p>\n<ul>\n<li>Bachelor’s Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 4+ years related experience (e.g., statistics predictive analytics, research) OR Master’s Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience (e.g., statistics, predictive analytics, research) OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 1+ year(s) related experience (e.g., statistics, predictive analytics, research) OR equivalent experience.</li>\n</ul>\n<p><strong>Technical skills:</strong></p>\n<ul>\n<li>Proven track record of deploying machine learning models in large-scale production environments.</li>\n<li>9+ years of experience building data pipelines, training deep learning models, and optimizing AI workflows.</li>\n</ul>\n<p><strong>Personal attributes:</strong></p>\n<ul>\n<li>Strong problem-solving skills and ability to work independently.</li>\n<li>Excellent communication and collaboration skills.</li>\n<li>Ability to work in a fast-paced environment and adapt to changing priorities.</li>\n</ul>\n<p><strong>Benefits</strong></p>\n<ul>\n<li>Competitive salary range: $119,800 - $234,700 per year.</li>\n<li>Comprehensive benefits package, including medical, dental, and vision insurance.</li>\n<li>401(k) matching program.</li>\n<li>Paid time off and holidays.</li>\n<li>Opportunities for professional growth and development.</li>\n<li>Collaborative and dynamic work environment.</li>\n</ul>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_d446c7ab-5f0","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Microsoft","sameAs":"https://microsoft.ai","logo":"https://logos.yubhub.co/microsoft.ai.png"},"x-apply-url":"https://microsoft.ai/job/member-of-technical-staff-applied-scientist-windows-copilot/","x-work-arrangement":"onsite","x-experience-level":"staff","x-job-type":"full-time","x-salary-range":"$119,800 - $234,700 per year","x-skills-required":["machine learning","deep learning","data pipelines","data curation","model development","deployment","iteration","research","statistics","econometrics","computer science","electrical engineering","computer engineering"],"x-skills-preferred":["proven track record of deploying machine learning models in large-scale production environments","9+ years of experience building data pipelines, training deep learning models, and optimizing AI workflows"],"datePosted":"2026-03-06T07:26:56.178Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Redmond"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"machine learning, deep learning, data pipelines, data curation, model development, deployment, iteration, research, statistics, econometrics, computer science, electrical engineering, computer engineering, proven track record of deploying machine learning models in large-scale production environments, 9+ years of experience building data pipelines, training deep learning models, and optimizing AI workflows","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":119800,"maxValue":234700,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_f0ed1b30-46f"},"title":"Senior Applied Scientist - Ads Click Prediction","description":"<p><strong>Summary</strong></p>\n<p>Microsoft are looking for a talented Senior Applied Scientist at their Suzhou office. This role sits at the heart of strategic decision-making, turning market data into actionable insights for a company that&#39;s revolutionising the online advertising platform and service. You&#39;ll work directly with leadership to shape the company&#39;s direction in the advertising industry.</p>\n<p><strong>About the Role</strong></p>\n<p>As a Senior Applied Scientist, you will play a key role in driving algorithmic and modeling improvement to the system. You will analyze performance and identify opportunities based on offline and online testing. You will develop and deliver robust and scalable solutions, make direct impact to both user and advertisers experience, and continually increase the revenue for Bing ads. You will have good communication, collaboration, and analytical skills.</p>\n<p><strong>Accountabilities</strong></p>\n<ul>\n<li>Play a key role in driving algorithmic and modeling improvement to the system.</li>\n<li>Analyze performance and identify opportunities based on offline and online testing.</li>\n</ul>\n<p><strong>The Candidate we&#39;re looking for</strong></p>\n<p><strong>Experience:</strong></p>\n<ul>\n<li>Bachelor’s Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 4+ years related experience (e.g., statistics predictive analytics, research) OR Master’s Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience (e.g., statistics, predictive analytics, research) OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 1+ year(s) related experience (e.g., statistics, predictive analytics, research) OR equivalent experience.</li>\n</ul>\n<p><strong>Technical skills:</strong></p>\n<ul>\n<li>Experience creating publications (e.g., patents, libraries, peer-reviewed academic papers).</li>\n<li>Experience presenting at conferences or other events in the outside research/industry community as an invited speaker.</li>\n<li>Experience conducting research as part of a research program (in academic or industry settings).</li>\n</ul>\n<p><strong>Personal attributes:</strong></p>\n<ul>\n<li>Strong analytical and problem-solving skills.</li>\n<li>Excellent communication and collaboration skills.</li>\n</ul>\n<p><strong>Benefits</strong></p>\n<ul>\n<li>Competitive salary.</li>\n<li>Comprehensive benefits package.</li>\n<li>Opportunities for professional growth and development.</li>\n</ul>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_f0ed1b30-46f","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Microsoft","sameAs":"https://microsoft.ai","logo":"https://logos.yubhub.co/microsoft.ai.png"},"x-apply-url":"https://microsoft.ai/job/senior-applied-scientist-ads-click-prediction-2/","x-work-arrangement":"onsite","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"Competitive salary","x-skills-required":["Statistics","Econometrics","Computer Science","Electrical or Computer Engineering","Predictive analytics","Research"],"x-skills-preferred":["Experience creating publications","Experience presenting at conferences","Experience conducting research"],"datePosted":"2026-03-06T07:26:23.056Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Suzhou"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, Predictive analytics, Research, Experience creating publications, Experience presenting at conferences, Experience conducting research"},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_0e124f59-bba"},"title":"Snr Applied Scientist","description":"<p><strong>Summary</strong></p>\n<p>Microsoft are looking for a talented Snr Applied Scientist at their Cairo office. This role sits at the heart of strategic decision-making, turning market data into actionable insights for a company that&#39;s revolutionising online shopping technology. You&#39;ll work directly with leadership to shape the company&#39;s direction in the global e-commerce market.</p>\n<p><strong>About the Role</strong></p>\n<p>As a Snr Applied Scientist in AI, and NLP, you will build top-notch models to solve a multitude of tasks core to building and enriching Microsoft Product Catalog. This opportunity will allow you to accelerate your career growth, develop deep problem-solving skills, collaborate with different team through active engagement with teams from different cultures.</p>\n<p><strong>Accountabilities</strong></p>\n<ul>\n<li>Master one or more subareas and gain expertise in a broad area of research, including applicable research techniques.</li>\n<li>Gain deep knowledge of a service, platform, or domain, and identify product needs by sharing the latest industry trends and applied technologies.</li>\n</ul>\n<p><strong>The Candidate we&#39;re looking for</strong></p>\n<p><strong>Experience:</strong></p>\n<ul>\n<li>Bachelor’s Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 4+ years related experience (e.g., statistics predictive analytics, research) OR Master’s Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience (e.g., statistics, predictive analytics, research) OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 1+ year(s) related experience (e.g., statistics, predictive analytics, research) OR equivalent experience.</li>\n</ul>\n<p><strong>Technical skills:</strong></p>\n<ul>\n<li>Master’s Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 6+ years related experience (e.g., statistics, predictive analytics, research) OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience (e.g., statistics, predictive analytics, research) OR equivalent experience.</li>\n</ul>\n<p><strong>Personal attributes:</strong></p>\n<ul>\n<li>3+ years experience creating publications (e.g., patents, libraries, peer-reviewed academic papers).</li>\n<li>Experience presenting at conferences or other events in the outside research/industry community as an invited speaker.</li>\n</ul>\n<p><strong>Benefits</strong></p>\n<ul>\n<li>Work arrangements (remote, hybrid, office-based).</li>\n<li>Health and wellbeing benefits.</li>\n<li>Professional development opportunities.</li>\n<li>Financial benefits (bonus, equity, pension, etc.).</li>\n<li>Cultural perks (team events, office amenities, etc.).</li>\n</ul>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_0e124f59-bba","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Microsoft","sameAs":"https://microsoft.ai","logo":"https://logos.yubhub.co/microsoft.ai.png"},"x-apply-url":"https://microsoft.ai/job/snr-applied-scientist/","x-work-arrangement":"onsite","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":null,"x-skills-required":["Statistics","Econometrics","Computer Science","Electrical or Computer Engineering","Research"],"x-skills-preferred":["Machine Learning","Data Science","Artificial Intelligence"],"datePosted":"2026-03-06T07:26:20.250Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Cairo"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, Research, Machine Learning, Data Science, Artificial Intelligence"},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_e099f6b4-585"},"title":"Principle Applied Scientist","description":"<p><strong>Summary</strong></p>\n<p>Microsoft are looking for a talented Principle Applied Scientist at their Beijing office. This role sits at the heart of strategic decision-making, turning market data into actionable insights for a company that&#39;s revolutionising the technology industry. You&#39;ll work directly with leadership to shape the company&#39;s direction in the global market.</p>\n<p><strong>About the Role</strong></p>\n<p>As a Principle Applied Scientist, you will play an important role in contributing to the development and optimization of our online services and offline pipelines within our content ecosystem to achieve product and business growth goals. Your primary responsibility will be to design, develop, and implement recommendation algorithms to deliver product features and drive user engagement. 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This role sits at the heart of strategic decision-making, turning market data into actionable insights for a company that&#39;s revolutionising online shopping technology. You&#39;ll work directly with leadership to shape the company&#39;s direction in the online shopping market.</p>\n<p><strong>About the Role</strong></p>\n<p>As a Snr Applied Scientist in AI, and NLP, you will build top-notch models to solve a multitude of tasks core to building and enriching Microsoft Product Catalog. This opportunity will allow you to accelerate your career growth, develop deep problem-solving skills, collaborate with different team through active engagement with teams from different cultures.</p>\n<p><strong>Accountabilities</strong></p>\n<ul>\n<li>Master one or more subareas and gain expertise in a broad area of research, including applicable research techniques.</li>\n<li>Gain deep knowledge of a service, platform, or domain, and identify product needs by sharing the latest industry trends and applied technologies.</li>\n</ul>\n<p><strong>The Candidate we&#39;re looking for</strong></p>\n<p><strong>Experience:</strong></p>\n<ul>\n<li>Bachelor’s Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 4+ years related experience (e.g., statistics predictive analytics, research) OR Master’s Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience (e.g., statistics, predictive analytics, research) OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 1+ year(s) related experience (e.g., statistics, predictive analytics, research) OR equivalent experience.</li>\n</ul>\n<p><strong>Technical skills:</strong></p>\n<ul>\n<li>Master’s Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 6+ years related experience (e.g., statistics, predictive analytics, research) OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience (e.g., statistics, predictive analytics, research) OR equivalent experience.</li>\n</ul>\n<p><strong>Personal attributes:</strong></p>\n<ul>\n<li>3+ years experience creating publications (e.g., patents, libraries, peer-reviewed academic papers).</li>\n<li>Experience presenting at conferences or other events in the outside research/industry community as an invited speaker.</li>\n<li>3+ years experience conducting research as part of a research program (in academic or industry settings).</li>\n</ul>\n<p><strong>Benefits</strong></p>\n<ul>\n<li>Work arrangements (remote, hybrid, office-based).</li>\n<li>Health and wellbeing benefits.</li>\n<li>Professional development opportunities.</li>\n<li>Financial benefits (bonus, equity, pension, etc.).</li>\n<li>Cultural perks (team events, office amenities, etc.).</li>\n</ul>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_5f8cde4b-a22","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Microsoft","sameAs":"https://microsoft.ai","logo":"https://logos.yubhub.co/microsoft.ai.png"},"x-apply-url":"https://microsoft.ai/job/snr-applied-scientist-2/","x-work-arrangement":"hybrid","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":null,"x-skills-required":["Statistics","Econometrics","Computer Science","Electrical or Computer Engineering","Research"],"x-skills-preferred":["Statistics","Econometrics","Computer Science","Electrical or Computer Engineering"],"datePosted":"2026-03-06T07:26:11.633Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Multiple Locations, Egypt"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, Research, Statistics, Econometrics, Computer Science, Electrical or Computer Engineering"},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_949a61a2-a0d"},"title":"Senior Applied Scientist - Ads Click Prediction","description":"<p><strong>Summary</strong></p>\n<p>Microsoft are looking for a talented Senior Applied Scientist at their Beijing office. This role sits at the heart of strategic decision-making, turning market data into actionable insights for a company that&#39;s revolutionising the online advertising platform and service. You&#39;ll work directly with leadership to shape the company&#39;s direction in the advertising market.</p>\n<p><strong>About the Role</strong></p>\n<p>As a Senior Applied Scientist, you will play a key role in driving algorithmic and modeling improvement to the system. You will analyze performance and identify opportunities based on offline and online testing. You will develop and deliver robust and scalable solutions, make direct impact to both user and advertisers experience, and continually increase the revenue for Bing ads. You will have good communication, collaboration, and analytical skills.</p>\n<p><strong>Accountabilities</strong></p>\n<ul>\n<li>Play a key role in driving algorithmic and modeling improvement to the system.</li>\n<li>Analyze performance and identify opportunities based on offline and online testing.</li>\n</ul>\n<p><strong>The Candidate we&#39;re looking for</strong></p>\n<p><strong>Experience:</strong></p>\n<ul>\n<li>Bachelor’s Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 4+ years related experience (e.g., statistics predictive analytics, research) OR Master’s Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience (e.g., statistics, predictive analytics, research) OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 1+ year(s) related experience (e.g., statistics, predictive analytics, research) OR equivalent experience.</li>\n</ul>\n<p><strong>Technical skills:</strong></p>\n<ul>\n<li>Experience creating publications (e.g., patents, libraries, peer-reviewed academic papers).</li>\n<li>Experience presenting at conferences or other events in the outside research/industry community as an invited speaker.</li>\n<li>Experience conducting research as part of a research program (in academic or industry settings).</li>\n</ul>\n<p><strong>Personal attributes:</strong></p>\n<ul>\n<li>Strong analytical and problem-solving skills.</li>\n<li>Excellent communication and collaboration skills.</li>\n</ul>\n<p><strong>Benefits</strong></p>\n<ul>\n<li>Competitive salary.</li>\n<li>Comprehensive benefits package.</li>\n<li>Opportunities for professional growth and development.</li>\n<li>Collaborative and dynamic work environment.</li>\n</ul>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_949a61a2-a0d","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Microsoft","sameAs":"https://microsoft.ai","logo":"https://logos.yubhub.co/microsoft.ai.png"},"x-apply-url":"https://microsoft.ai/job/senior-applied-scientist-ads-click-prediction/","x-work-arrangement":"onsite","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"Competitive salary","x-skills-required":["Statistics","Econometrics","Computer Science","Electrical or Computer Engineering","Predictive analytics","Research"],"x-skills-preferred":["Experience creating publications","Experience presenting at conferences","Experience conducting research"],"datePosted":"2026-03-06T07:26:06.345Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Beijing"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, Predictive analytics, Research, Experience creating publications, Experience presenting at conferences, Experience conducting research"},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_b75c2ed4-d29"},"title":"Principal Applied Scientist","description":"<p><strong>Summary</strong></p>\n<p>Microsoft AI are looking for a talented Principal Applied Scientist at their Redmond office. This role sits at the heart of strategic decision-making, transforming complex data into actionable insights for a company that&#39;s revolutionising the field of artificial intelligence. You&#39;ll work directly with leadership to shape the company&#39;s direction in the development of large-scale, Azure-based intelligence platforms.</p>\n<p><strong>About the Role</strong></p>\n<p>As a Principal Applied Scientist, you will define scientific vision and lead the development of both ML and LLM components. This includes designing robust models, driving experimentation, ensuring statistical rigor, and guiding the platform&#39;s evolution toward greater automation, accuracy, and scalability. 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This role sits at the heart of strategic decision-making, turning market data into actionable insights for a company that&#39;s revolutionising AI technologies. You&#39;ll work directly with leadership to shape the company&#39;s direction in the search and AI innovation markets.</p>\n<p><strong>About the Role</strong></p>\n<p>We are looking for a Senior Applied Scientist to design and build scalable, high-performance platform and grounding services for real-time processing of streaming news content and serving user queries with low latency. You will apply AI and machine learning to solve challenging problems in news Index, content understanding, query understanding, trending detection, ranking, and quality improvement for relevance, freshness, and authority, especially for grounding scenario. You will act as a designated responsible individual (DRI), work with partners and v-team members to understand requirements, define roadmap, lead execution, unblock issues, deliver mission on time. You will proactively learn and leverage engineer excellence practice from partner teams, build collaboration with partners. 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This role sits at the heart of advanced AI at web scale, shaping the future of key systems within Microsoft Ads, Copilot, and beyond. The work will directly impact millions of users and advertisers by delivering scalable solutions that enhance ad relevance and optimize user and advertiser experiences.</p>\n<p><strong>About the Role</strong></p>\n<p>In this role, the Senior Applied Scientist will design and implement state-of-the-art machine learning models and algorithms that power key systems within Microsoft Ads, Copilot, and beyond. The work will directly impact millions of users and advertisers by delivering scalable solutions that enhance ad relevance and optimize user and advertiser experiences. Responsibilities span the full modeling lifecycle, including training data and labeling strategy, feature and signal design, model development, and rigorous offline and online evaluation. Engineers and applied scientists work closely at the intersection of machine learning, economics, and large-scale systems to deliver high-performance real-time inference and robust experimentation in production.</p>\n<p><strong>Accountabilities</strong></p>\n<ul>\n<li>Develop and deploy cutting-edge machine learning models, including transformers, generative AI, and reinforcement learning, to optimize user interactions and ad relevance across Microsoft Ads and Copilot.</li>\n<li>Design scalable algorithms for online and offline systems, delivering innovative solutions for ads selection, ad generation and ad relevance.</li>\n<li>Drive experimentation through A/B testing and offline validation to evaluate model performance and refine user behavior predictions.</li>\n<li>Build robust data pipelines and frameworks for handling large-scale, high-dimensional datasets to support advanced AI applications.</li>\n<li>Stay at the forefront of AI research, incorporating the latest advancements to drive innovation and impact across Microsoft platforms.</li>\n</ul>\n<p><strong>The Candidate we&#39;re looking for</strong></p>\n<p><strong>Experience:</strong></p>\n<ul>\n<li>Bachelor’s Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 4+ years related experience (e.g., statistics predictive analytics, research) OR Master’s Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience (e.g., statistics, predictive analytics, research) OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 1+ year(s) related experience (e.g., statistics, predictive analytics, research) OR equivalent experience.</li>\n</ul>\n<p><strong>Technical skills:</strong></p>\n<ul>\n<li>Proven experience in programming and data analysis skills.</li>\n<li>Proven expertise in the areas of Generative AI, deep learning, Reinforcement learning, transformers or LLM.</li>\n<li>5+ years of experience in developing and deploying large-scale machine learning models.</li>\n</ul>\n<p><strong>Personal attributes:</strong></p>\n<ul>\n<li>Strong problem-solving skills and ability to work independently.</li>\n<li>Excellent communication and collaboration skills.</li>\n<li>Ability to work in a fast-paced environment and adapt to changing priorities.</li>\n</ul>\n<p><strong>Benefits</strong></p>\n<ul>\n<li>Competitive salary range of CAD $114,400 – CAD $203,900 per year.</li>\n<li>Comprehensive benefits package, including health, dental, and vision insurance.</li>\n<li>Opportunities for professional development and growth within the company.</li>\n<li>Collaborative and dynamic work environment.</li>\n<li>Access to cutting-edge technology and resources.</li>\n<li>Flexible work arrangements, including remote work options.</li>\n</ul>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_05ddca1c-456","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Microsoft AI","sameAs":"https://microsoft.ai","logo":"https://logos.yubhub.co/microsoft.ai.png"},"x-apply-url":"https://microsoft.ai/job/senior-applied-scientist-17/","x-work-arrangement":"hybrid","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"CAD $114,400 – CAD $203,900 per year","x-skills-required":["machine learning","statistics","econometrics","computer science","electrical or computer engineering","programming","data analysis","generative AI","deep learning","reinforcement learning","transformers","LLM"],"x-skills-preferred":["problem-solving","communication","collaboration","adaptability"],"datePosted":"2026-03-05T19:50:12.889Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Toronto"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"machine learning, statistics, econometrics, computer science, electrical or computer engineering, programming, data analysis, generative AI, deep learning, reinforcement learning, transformers, LLM, problem-solving, communication, collaboration, adaptability","baseSalary":{"@type":"MonetaryAmount","currency":"CAD","value":{"@type":"QuantitativeValue","minValue":114400,"maxValue":203900,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_9b2262ac-604"},"title":"Senior Applied Scientist","description":"<p><strong>Summary</strong></p>\n<p>Microsoft AI are looking for a talented Senior Applied Scientist at their Redmond office. This role sits at the heart of advanced AI at web scale, shaping the future of key systems within Microsoft Ads, Copilot, and beyond. You&#39;ll design and implement state-of-the-art machine learning models and algorithms that power scalable solutions that enhance ad relevance and optimize user and advertiser experiences.</p>\n<p><strong>About the Role</strong></p>\n<p>In this role, you will develop and deploy cutting-edge machine learning models, including transformers, generative AI, and reinforcement learning, to optimize user interactions and ad relevance across Microsoft Ads and Copilot. You will design scalable algorithms for online and offline systems, delivering innovative solutions for ads selection, ad generation, and ad relevance. You will drive experimentation through A/B testing and offline validation to evaluate model performance and refine user behavior predictions. You will build robust data pipelines and frameworks for handling large-scale, high-dimensional datasets to support advanced AI applications. You will stay at the forefront of AI research, incorporating the latest advancements to drive innovation and impact across Microsoft platforms.</p>\n<p><strong>Accountabilities</strong></p>\n<ul>\n<li>Develop and deploy cutting-edge machine learning models, including transformers, generative AI, and reinforcement learning, to optimize user interactions and ad relevance across Microsoft Ads and Copilot.</li>\n<li>Design scalable algorithms for online and offline systems, delivering innovative solutions for ads selection, ad generation, and ad relevance.</li>\n<li>Drive experimentation through A/B testing and offline validation to evaluate model performance and refine user behavior predictions.</li>\n<li>Build robust data pipelines and frameworks for handling large-scale, high-dimensional datasets to support advanced AI applications.</li>\n</ul>\n<p><strong>The Candidate we&#39;re looking for</strong></p>\n<p><strong>Experience:</strong></p>\n<ul>\n<li>Bachelor’s Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 4+ years related experience (e.g., statistics predictive analytics, research) OR Master’s Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience (e.g., statistics, predictive analytics, research) OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 1+ year(s) related experience (e.g., statistics, predictive analytics, research) OR equivalent experience.</li>\n</ul>\n<p><strong>Technical skills:</strong></p>\n<ul>\n<li>Proven experience in programming and data analysis skills.</li>\n<li>Proven expertise in the areas of Generative AI, deep learning, Reinforcement learning, transformers or LLM.</li>\n</ul>\n<p><strong>Personal attributes:</strong></p>\n<ul>\n<li>Strong problem-solving skills and ability to work independently.</li>\n<li>Excellent communication and collaboration skills.</li>\n</ul>\n<p><strong>Benefits</strong></p>\n<ul>\n<li>Competitive salary presumption of $119,800 - $234,700 per year.</li>\n<li>Comprehensive benefits package, including medical, dental, and vision insurance.</li>\n<li>401(k) matching program.</li>\n<li>Paid time off and holidays.</li>\n<li>Opportunities for professional growth and development.</li>\n</ul>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_9b2262ac-604","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Microsoft AI","sameAs":"https://microsoft.ai","logo":"https://logos.yubhub.co/microsoft.ai.png"},"x-apply-url":"https://microsoft.ai/job/senior-applied-scientist-18/","x-work-arrangement":"onsite","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$119,800 - $234,700 per year","x-skills-required":["machine learning","artificial intelligence","data analysis","programming","statistics","econometrics","computer science","electrical engineering"],"x-skills-preferred":["generative AI","deep learning","reinforcement learning","transformers","LLM"],"datePosted":"2026-03-05T19:46:18.960Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Redmond"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"machine learning, artificial intelligence, data analysis, programming, statistics, econometrics, computer science, electrical engineering, generative AI, deep learning, reinforcement learning, transformers, LLM","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":119800,"maxValue":234700,"unitText":"YEAR"}}}]}