Your primary responsibilities will be to:

• Guide the development of highly connected data systems that enable data-driven, model-based analytics to improve pipeline effectiveness and efficiency;
• Work with multifunctional teams to enable data connectivity across the editing pipeline, integrating information from lab, greenhouse, and field operations;
• Collaborate with partner teams across Crop Science (Gene Editing, IT Enterprise, Data and Engineering) to automate decision making and improve operational efficiency to accelerate development of gene-edited products;
• Serve as a key communicator translating business data knowledge and operational workflows into clear technical implementation plans for data scientists, data engineers, and developers;
• Demonstrate autonomy in building relationships and networks within your unit and across functions, most often with members of the Crop Genome Editing team and closely aligned partner teams;
• Act as a consultant to leadership and colleagues on digital strategy and data-driven operations through clear, organized, and influential communication;
• Actively build your own acumen in biology, genome design, and digital operations while sharing best practices and learnings with the broader Biology and Genome Design community.

We seek an incumbent who possesses the following qualifications:

• PhD in Computational Biology, Computer Science and Engineering, or another relevant scientific field with a minimum of 6 years of relevant experience, or MS with 10+ years of relevant experience;
• Demonstrated track record developing data systems and pipelines that enable efficient product delivery and operational modeling;
• Demonstrated experience working collaboratively in cross-functional and cross-cultural teams to achieve common goals;
• Demonstrated experience leading and influencing activities of cross-functional teams without direct reporting relationships;
• Ability to lead and influence key stakeholders through challenges and opportunities and to facilitate solutions.

Preferred qualifications include experience building data pipelines as a ML DevOps Engineer or Data Engineer, experience with Operations Research, and experience analyzing large biological datasets and developing analytical pipelines using Python, R, or similar software and languages.

XML job scraping automation by YubHub

Responsibilities:

• Inspire, lead, and grow a team of data scientists to achieve our longer-term vision
• Drive data science projects end-to-end in partnership with Product, Engineering, and other partners to inform product strategy and investment decisions
• Analyze large datasets to identify trends, patterns, and insights that can help understand marketplace dynamics and help cross-functional teams (e.g., product, engineering, marketing) to define and execute data-driven optimization strategies
• Actively influence the design of the strategy and shaping of the roadmap. Generate and use team insights to set and prioritise longer-term goals
• Create and implement A/B testing, experimentation, and other cutting-edge statistical/mathematical frameworks to analyse Ads (marketplace) performance
• Continually develop & execute on a Data Science roadmap and vision for your team
• Stay abreast of industry best practices and emerging technologies in the field of advertising and data science
• Foster a culture of innovation, collaboration, and technical excellence
• Be an integral part of the Data Science Org, leveraging and contributing to the vibrant knowledge base, shared across a community of world-class data experts

Required Qualifications:

• PhD or Master's degree in Economics, Statistics, Machine Learning, Operations Research, or other quantitative fields
• 4+ years of management experience. Experience managing managers is a bonus
• Strong skills in programming (Python or R) and SQL
• Experience in leveraging AI-assisted development tools (e.g., Cursor, Claude, or similar LLMs) to improve personal and team productivity, code quality, and technical problem-solving
• Deep understanding of Ads Marketplace
• Extensive experience of online experimentation and causal inference
• Ability to communicate & discuss low-level technical topics as well as high-level strategies
• Comfortable in innovative and fast-paced environments, and an innate ability to bias toward action
• Results-oriented with a strong customer and business focus
• Track-record driving product roadmap and execution with strong cross-org collaborations
• Ability to provide structure and tackle ambiguous and undefined problems

Benefits:

• Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support
• Family Planning Support
• Gender-Affirming Care
• Mental Health & Coaching Benefits
• Comprehensive Medical Benefits & Health Care Spending Account
• Registered Retirement Savings Plan with matching contributions
• Income Replacement Programs
• Flexible Vacation & Paid Volunteer Time Off
• Generous Paid Parental Leave

XML job scraping automation by YubHub

You have technical depth and business knowledge and can drive complex technology discussions which express the value of the Databricks platform throughout the sales lifecycle.

In partnership with our Account Executives, you will engage with our customers' technical leads, including architects, engineers, and operations teams with the goal of establishing yourself as a trusted advisor to achieve tangible outcomes.

You will work with teams across Databricks and our executive leadership to represent your customer's needs and build valuable customer engagements and report to the Field Engineering Manager.

The impact you will have:

• Work with Sales and other essential partners to develop account strategies for your assigned accounts to grow their usage of the platform.

• Establish the Databricks Lakehouse architecture as the standard data architecture for customers through excellent technical account planning.

• Build and present reference architectures and demo applications for prospects to help them understand how Databricks can be used to achieve their goals to land new users and use cases.

• Capture the technical win by consulting on big data architectures, data engineering pipelines, and data science/machine learning projects; prove out the Databricks technology for strategic customer projects; and validate integrations with cloud services and other 3rd party applications.

• Become an expert in, and promote Databricks inspired open-source projects (Spark, Delta Lake, MLflow, and Koalas) across developer communities through meetups, conferences, and webinars.

What we look for:

• 5+ years in a customer-facing pre-sales, technical architecture, or consulting role with expertise in at least one of the following technologies:

• Big data engineering (Ex: Spark, Hadoop, Kafka)

• Data Warehousing & ETL (Ex: SQL, OLTP/OLAP/DSS)

• Data Science and Machine Learning (Ex: pandas, scikit-learn, HPO)

• Data Applications (Ex: Logs Analysis, Threat Detection, Real-time Systems Monitoring, Risk Analysis and more)

• Experience translating a customer's business needs to technology solutions, including establishing buy-in with essential customer stakeholders at all levels of the business.

• Experienced at designing, architecting, and presenting data systems for customers and managing the delivery of production solutions of those data architectures.

• Fluent in SQL and database technology.

• Debug and development experience in at least one of the following languages: Python, Scala, Java, or R.

• Desired: Built solutions with public cloud providers such as AWS, Azure, or GCP

• Desired: Degree in a quantitative discipline (Computer Science, Applied Mathematics, Operations Research)

• Travel to customers in your region up to 30% of the time.

XML job scraping automation by YubHub

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.

In addition, you will leverage Airbnb'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's community safe and trusted.

Key responsibilities include:

• Leading and driving data-driven roadmaps for the CS Safety working groups
• Recommending actionable solutions backed by data and metrics to product and operational problems
• 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
• Performing data modelling of the various entities using tools and frameworks for optimising community and agent experiences
• Defining and evaluating key metrics in an unstructured problem space, including measurement of the ML models that drive product development
• Anticipating emerging safety risks through early-warning indicators, trend analysis, predictive modelling, and scenario planning to assess operational risk
• Influencing data-driven decisions across business verticals in day-to-day via business reviews, scorecards, self-serve portal, OKRs, and planning among others
• Influencing experimentation and measurement strategies; conducting power analyses, defining exit criteria, and using statistical models to improve inference

Requirements include:

• 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)
• Experience supporting safety, risk, Trust & Safety, compliance, or employee wellbeing in high-volume call centre or customer operations environments
• Expert skills in SQL and expert in at least one programming language for data analysis (Python or R)
• Experience with non-experimental causal inference methods, experimentation, and machine learning techniques, ideally in a multi-sided platform setting
• Working knowledge of schema design and high-dimensional data modelling (ETL framework like Airflow)
• Ability to work under conditions of ambiguity in a fast-growth, sometimes uncertain and complex environment
• Comfortable operating independently with minimal planning, direction, and supervision
• Proven track record of influencing senior leaders and driving outcomes

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

XML job scraping automation by YubHub

Job Description: The AI Forward Deployed Engineering (AI FDE) team is a highly specialized customer-facing AI team at Databricks. We deliver professional services engagements to help our federal government customers build and productionize first-of-its-kind AI applications.

Responsibilities:

• Develop cutting-edge GenAI solutions, incorporating the latest techniques from our Mosaic AI Research to solve customer problems.
• Own production rollouts of consumer and internally facing GenAI applications.
• Serve as a trusted technical advisor to customers across a variety of domains.
• Present at conferences such as Data + AI Summit, recognized as a thought leader internally and externally.
• Collaborate cross-functionally with the product and engineering teams to influence priorities and shape the product roadmap.

What We Look For:

• Experience working with U.S. federal civilian, state, or local agencies.
• Experience building GenAI applications, including RAG, multi-agent systems, Text2SQL, fine-tuning, etc., with tools such as HuggingFace, LangChain, and DSPy.
• Expertise in deploying production-grade GenAI applications, including evaluation and optimizations.
• Extensive years of hands-on industry data science experience, leveraging common machine learning and data science tools (i.e., pandas, scikit-learn, PyTorch, etc.).
• Experience building production-grade machine learning deployments on AWS, Azure, or GCP.
• Graduate degree in a quantitative discipline (Computer Science, Engineering, Statistics, Operations Research, etc.) or equivalent practical experience.
• Experience communicating and/or teaching technical concepts to non-technical and technical audiences alike.
• Passion for collaboration, life-long learning, and driving business value through AI.

Pay Range Transparency:

Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected salary range for non-commissionable roles or on-target earnings for commissionable roles.

Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location.

Based on the factors above, Databricks anticipates utilizing the full width of the range.

The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above.

For more information regarding which range your location is in visit our page here.

Local Pay Range $180,656-$248,360 USD

Benefits:

At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees.

For specific details on the benefits offered in your region click here.

Our Commitment to Diversity and Inclusion:

At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel.

We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards.

Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics.

Compliance:

If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.

XML job scraping automation by YubHub

Responsibilities:

• Inspire, lead, and grow a team of data scientists to achieve our longer-term vision
• Drive data science projects end-to-end in partnership with Product, Engineering, and other partners to inform product strategy and investment decisions
• Analyze large datasets to identify trends, patterns, and insights that can help understand marketplace dynamics and help cross-functional teams (e.g., product, engineering, marketing) to define and execute data-driven optimization strategies
• Actively influence the design of the strategy and shaping of the roadmap. Generate and use team insights to set and prioritise longer-term goals
• Create and implement A/B testing, experimentation, and other cutting-edge statistical/mathematical frameworks to analyse Ads (marketplace) performance
• Continually develop & execute on a Data Science roadmap and vision for your team
• Stay abreast of industry best practices and emerging technologies in the field of advertising and data science
• Foster a culture of innovation, collaboration, and technical excellence
• Be an integral part of the Data Science Org, leveraging and contributing to the vibrant knowledge base, shared across a community of world-class data experts

Required Qualifications:

• PhD or Master's degree in Economics, Statistics, Machine Learning, Operations Research, or other quantitative fields
• 4+ years of management experience. Experience managing managers is a bonus
• Strong skills in programming (Python or R) and SQL
• Experience in leveraging AI-assisted development tools (e.g., Cursor, Claude, or similar LLMs) to improve personal and team productivity, code quality, and technical problem-solving
• Deep understanding of Ads Marketplace
• Extensive experience of online experimentation and causal inference
• Ability to communicate & discuss low-level technical topics as well as high-level strategies
• Comfortable in innovative and fast-paced environments, and an innate ability to bias toward action
• Results-oriented with a strong customer and business focus
• Track-record driving product roadmap and execution with strong cross-org collaborations
• Ability to provide structure and tackle ambiguous and undefined problems

Benefits:

• Comprehensive Healthcare Benefits and Income Replacement Programs
• 401k with Employer Match
• Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support
• Family Planning Support
• Gender-Affirming Care
• Mental Health & Coaching Benefits
• Flexible Vacation & Paid Volunteer Time Off
• Generous Paid Parental Leave

XML job scraping automation by YubHub

You will use simulation and modeling tools to visualize production systems, identify bottlenecks, and optimize resource allocation,translating analytical insights into actionable production control decisions.

This is a hands-on role for someone with strong Operations Research fundamentals who is eager to apply simulation, optimization, and scripting to real manufacturing problems at scale.

Responsibilities:

• Develop and maintain discrete event simulation (DES) models of maritime manufacturing processes to support production planning and facility layout decisions
• Build and operate critical chain project management models to drive production scheduling and resource leveling
• Write scripts and build technology-driven workflows to automate production control tasks and streamline planning processes
• Collaborate with manufacturing technology teams to validate simulation assumptions against physical reality and implement process improvements
• Provide data-driven analysis to support capital equipment investments, make-vs-buy decisions, and capacity planning
• Create visualizations and reports that enable cross-functional teams (design, ops, finance, leadership) to understand factory behavior and make informed decisions
• Identify production bottlenecks, resource conflicts, and capacity constraints before they become expensive problems

Required Qualifications:

• Bachelor's degree in Industrial Engineering, Operations Research, Manufacturing Engineering, Systems Engineering, or related technical field
• 2+ years of experience in simulation modeling, production planning, or industrial engineering
• Foundational knowledge of discrete event simulation concepts and at least one DES platform (FlexSim, Simio, AnyLogic, Arena, or equivalent)
• Strong analytical skills with the ability to translate complex data into actionable insights
• Willingness to integrate new technology into workflows , writing scripts, automating processes, and adopting tools that accelerate the team
• Proficiency in data analysis and visualization tools (Python, Excel, or similar)
• Ability to work directly with manufacturing teams to implement process improvements based on simulation and analytical results
• Eligible to obtain and maintain an active U.S. Secret security clearance

Preferred Qualifications:

• Master's degree or coursework emphasis in Operations Research, simulation, or optimization
• Experience with critical chain project management concepts or tools (Aurora from Stottler Henke, ProChain, or similar)
• Experience scripting or building automated workflows to support production planning or engineering processes
• Familiarity with manufacturing environments,shipyard, aerospace, defense, or advanced manufacturing
• Programming skills in Python for custom analysis, automation, and integration
• Knowledge of Lean manufacturing, Theory of Constraints, or Six Sigma methodologies
• Experience with digital twin concepts or integration of simulation with production systems (MES/ERP)
• Internship or project experience in factory layout, capacity planning, or production scheduling

US Salary Range $86,000-$114,000 USD

XML job scraping automation by YubHub

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 & 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.).

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'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.

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.

Responsibilities:

• Use proprietary annotation and evaluation software to deliver accurate labels, rankings, critiques, and comprehensive solutions on assigned projects
• Consistently produce high-quality, curated data that adheres to strict quantitative and regulatory standards
• Collaborate with engineers and researchers to develop and iterate on new training tasks, risk-specific benchmarks, and evaluation frameworks
• Provide constructive feedback to improve the efficiency, precision, and usability of annotation and data-collection tools
• Select and solve challenging problems from financial risk domains where you have deep expertise

Basic Qualifications:

• 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
• Excellent written and verbal English communication (technical reports, regulatory documentation, explanatory breakdowns)
• Strong familiarity with financial risk data sources and platforms (Bloomberg, Refinitiv, Moody’s Analytics, S&P Capital IQ, RiskMetrics, internal bank risk systems, regulatory filings, Basel/FRB datasets, etc.)
• Exceptional analytical reasoning, attention to detail, and ability to exercise sound judgment with incomplete or ambiguous data

Preferred Skills and Experience:

• 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
• Track record of publication(s) or contributions in refereed journals/conferences on risk, econometrics, statistics, or quantitative finance
• Prior teaching, mentoring, or training experience (university, industry workshops, regulatory training)
• Proficiency in Python/R for risk modeling (pandas, NumPy, SciPy, statsmodels, QuantLib, PyTorch/TensorFlow for ML risk models, etc.) and familiarity with risk systems (Murex, Calypso, Numerix, etc.)
• Experience with Monte Carlo simulation, copula models, stochastic processes, time-series analysis, extreme value theory, or machine learning for risk (anomaly detection, credit scoring, etc.)
• Knowledge of regulatory capital frameworks (Basel III/IV, FRB CCAR, SR 11-7 model risk guidance, IFRS 9/CECL, Solvency II)
• CFA, FRM, PRM, CQF, or similar risk-focused certifications
• Previous exposure to large language models, AI safety, or quantitative evaluation pipelines

Location and Other Expectations:

• Tutor roles may be offered as full-time, part-time, or contractor positions, depending on role needs and candidate fit
• For contractor positions, hours will vary widely based on project scope and contractor availability, with no fixed commitments required
• Tutor roles may be performed remotely from any location worldwide, subject to legal eligibility, time-zone compatibility, and role specific needs
• For US based candidates, please note we are unable to hire in the states of Wyoming and Illinois at this time
• We are unable to provide visa sponsorship
• For those who will be working from a personal device, your computer must meet xAI’s minimum hardware requirements

XML job scraping automation by YubHub

You'll collaborate with our technical team to train models on human interactions, problem-solving, and discussions; refine annotation tools; and select/create challenging applied math problems to boost performance.

Responsibilities:

• Use proprietary software applications to provide input/labels on defined projects.
• Support and ensure the delivery of high-quality curated data.
• Play a pivotal role in supporting and contributing to the training of new tasks, working closely with the technical staff to ensure the successful development and implementation of cutting-edge initiatives/technologies.
• Interact with the technical staff to help improve the design of efficient annotation tools.
• Choose problems from applied math domains that align with your expertise, focusing on areas such as probability, statistics, numerical analysis, optimization, operations research, dynamical systems, data modeling, and related fields where you can confidently provide detailed solutions and evaluate model responses.

Basic Qualifications:

• Must have either (a) a Master’s or PhD in Mathematics with a specialization in a subdomain of applied mathematics (there is a separate position for pure math) or (b) a medal in an International Math Olympiad (IMO) or similar level math competition.
• Proficiency in reading and writing, both in informal and professional English.
• Strong ability to navigate various information resources and databases.
• Outstanding communication, interpersonal, analytical, and organizational capabilities.
• Solid reading comprehension skills combined with capacity to exercise autonomous judgment even when presented with limited data/material.
• A strong passion for and commitment to technological advancements and innovation.

Preferred Skills and Experience:

• Math PhD with a specialization in a subdomain of applied mathematics.
• Peer-reviewed applied math publications in well-regarded journals.
• Previous AI Tutoring experience and/or experience teaching college courses.

Location and Other Expectations:

• Tutor roles may be offered as full-time, part-time, or contractor positions, depending on role needs and candidate fit.
• For contractor positions, hours will vary widely based on project scope and contractor availability, with no fixed commitments required. On average most projects may involve at least 10 hours per week to achieve deliverables effectively though this is not a fixed commitment and depends on the scope of work. Contractors have full flexibility to set their own hours and determine the exact amount of time needed to complete deliverables.
• Tutor roles may be performed remotely from any location worldwide, subject to legal eligibility, time-zone compatibility, and role specific needs.
• For US based candidates, please note we are unable to hire in the states of Wyoming and Illinois at this time.
• We are unable to provide visa sponsorship.
• For those who will be working from a personal device, your computer must be a Chromebook, Mac with MacOS 11.0 or later, or Windows 10 or later.

Compensation and Benefits:

US based candidates: $45/hour - $75/hour depending on factors including relevant experience, skills, education, geographic location, and qualifications. International candidates: Information will be provided to you during the recruitment process.

Benefits vary based on employment type, location and jurisdiction. Benefits for eligible U.S. based positions include health insurance, 401(k) plan, and paid sick leave. Specific details and role specific information will be provided to you during the interview process.

XML job scraping automation by YubHub

Your deep domain knowledge will guide the selection and rigorous solving of complex problems in quantitative crypto strategies , including on-chain analysis, DeFi protocols, perpetual futures & derivatives trading, cross-exchange arbitrage, market microstructure in fragmented venues, MEV-aware execution, machine learning for crypto alpha signals, and portfolio/risk management in high-volatility 24/7 markets.

This role demands sharp quantitative thinking, quick adaptation to evolving instructions, and the ability to deliver precise, technically robust critiques and solutions in a dynamic environment.

Responsibilities:

• Utilize proprietary software to deliver accurate labels, rankings, critiques, and in-depth solutions on assigned projects
• Consistently produce high-quality, curated data adhering to rigorous technical and domain standards
• Partner with engineers and researchers to iterate on new training tasks, evaluation frameworks, and crypto-specific benchmarks
• Offer actionable feedback to enhance the efficiency, accuracy, and usability of annotation and data-collection interfaces
• Identify and solve challenging problems from crypto & digital asset domains where you have strong expertise , examples include:

• On-chain metrics analysis and wallet/flow clustering for alpha generation
• DeFi yield farming, liquidity provision, and impermanent loss modeling
• Cross-exchange / CEX-DEX arbitrage and triangular opportunities
• Perpetual futures funding rate strategies and basis trading
• Market microstructure in crypto order books (fragmented liquidity, MEV, sandwich attacks)
• Machine learning models for price prediction, sentiment from social/on-chain, volatility forecasting
• Tokenomics evaluation, airdrop/IDO quantitative assessment, and risk premia in altcoins
• Portfolio optimization and risk management in 24/7 high-volatility environments

• Provide rigorous critiques of model outputs, alternative quantitative approaches, mathematical derivations, code snippets, and step-by-step crypto reasoning
• Efficiently interpret, analyze, and complete tasks based on detailed (and evolving) guidelines

Basic Qualifications:

• Master’s or PhD in a quantitative discipline: Quantitative Finance, Financial Engineering, Computer Science (with crypto/blockchain focus), Statistics, Applied Mathematics, Economics (quantitative), Physics, Operations Research, Data Science, or closely related field or equivalent professional experience as a quantitative crypto trader, systematic strategist, or on-chain analyst
• Superior written and verbal English communication (technical papers, explanatory breakdowns, professional correspondence)
• Extensive hands-on familiarity with crypto data sources and tools (CoinGecko, CoinMarketCap, Dune Analytics, Glassnode, Nansen, Chainalysis, Messari, DefiLlama, The Graph, blockchain explorers, CEX APIs, on-chain datasets, etc.)
• Outstanding analytical skills, attention to detail, and sound judgment under partial information

Preferred Skills and Experience:

• Professional experience in quantitative crypto trading, systematic strategies, or on-chain research at a crypto hedge fund, prop desk, market-making firm, DeFi protocol, or digital asset investment firm
• Publications or public analyses in crypto quant topics (e.g., journals, conferences, reputable blogs, GitHub repos with notable traction)
• Teaching, mentoring, or content-creation experience in crypto/quant finance (university, bootcamps, Twitter threads, newsletters)
• Proficiency in Python for crypto analysis (pandas, NumPy, ccxt, web3.py, etherscan APIs, polars, scikit-learn, PyTorch/TensorFlow for ML models, etc.) and/or Rust/Solidity familiarity
• Experience with backtesting crypto strategies, handling tick-level or on-chain data, managing API rate limits, and dealing with 24/7 market quirks
• Knowledge of MEV, flash loans, oracle manipulation risks, liquidation cascades, or other crypto-native phenomena
• CFA, FRM, CQF, or blockchain-specific certifications (e.g., Certified Blockchain Expert)
• Prior involvement with LLMs, reinforcement learning, or AI evaluation in financial/crypto contexts (strong plus)

Location and Other Expectations:

• Tutor roles may be offered as full-time, part-time, or contractor positions, depending on role needs and candidate fit.
• For contractor positions, hours will vary widely based on project scope and contractor availability, with no fixed commitments required. On average most projects may involve at least 10 hours per week to achieve deliverables effectively though this is not a fixed commitment and depends on the scope of work.
• Tutor roles may be performed remotely from any location worldwide, subject to legal eligibility, time-zone compatibility, and role specific needs.
• For US based candidates, please note we are unable to hire in the states of Wyoming and Illinois at this time.
• We are unable to provide visa sponsorship.
• For those who will be working from a personal device, your computer must be a Chromebook, Mac with MacOS 11.0 or later, or Windows 10 or later.

Compensation and Benefits:

US based candidates: $45/hour - $100/hour depending on factors including relevant experience, skills, education, geographic location, and qualifications. International candidates: $25/hour - $75/hour depending on factors including relevant experience, skills, education, geographic location, and qualifications.

XML job scraping automation by YubHub

Responsibilities:

• Design end-to-end human flow systems across physical environments (facilities, venues, campuses, events, transportation nodes, etc.)
• Architect queuing strategies (physical and digital) that optimise both actual and perceived wait times
• Identify and eliminate bottlenecks across movement, decision points, and service interactions
• Translate behavioural insights into practical, buildable system designs
• Partner with engineering, operations, facilities, and product teams to integrate human flow into system architecture
• Use data, observation, and simulation to model capacity, throughput, and edge cases
• Define principles for wayfinding, signage, pacing, and spatial cues
• Stress-test systems for peak load, abnormal conditions, and failure modes
• Document designs clearly so they can be executed, operated, and scaled
• Continuously iterate based on real-world performance and user behaviour

What Success Looks Like:

• People move through complex environments with minimal confusion or friction
• Systems handle peak demand gracefully without heroics or last-minute workarounds
• Operations teams trust and rely on your designs
• Leaders can make decisions using your models and recommendations
• Users rarely notice your work , except that “it just works”

Who You Are:

• You think in systems, not artifacts
• You are deeply curious about how people actually behave, not how plans assume they will
• You’re comfortable balancing empathy with constraints like safety, cost, and throughput
• You can move between strategy and details without losing coherence
• You communicate clearly with both technical and non-technical partners
• You’re opinionated, but evidence-driven

Qualifications:

• We care more about how you think than where you come from. Relevant backgrounds include:
  • Human Factors Engineering
  • Industrial / Systems Engineering
  • Experience Design (physical environments)
  • Operations Research
  • Architecture or Urban Planning (with operational exposure)
  • Theme parks, airports, transit systems, large venues, manufacturing, or high-scale operations

Typical qualifications:

• 7+ years designing or operating complex human-centered systems
• Experience with capacity modeling, service design, or pedestrian flow
• Familiarity with simulation tools or data-driven decision-making
• Proven ability to influence cross-functional teams without direct authority

Bonus Points:

• Experience designing systems under extreme peak loads
• Familiarity with crowd modeling or queuing theory
• Background in environments where safety is mission-critical
• Ability to prototype or test concepts quickly in the field
• A portfolio of systems you’ve designed that still work years later

Additional Information:

• Benefits: Medical Insurance, Dental and Vision Insurance, Time Off, Parental Leave, Competitive Salary, Retirement Plan, Stock Options, Life and Disability Insurance, Pet Insurance
• Saronic CCPA Notice for Candidates and California Employees: This role requires access to export-controlled information or items that require “U.S. Person” status.

XML job scraping automation by YubHub

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'll work on prompt engineering, implement modern language models techniques like Retrieval Augmented Generation, and create scalable workflows for measurement and evaluation.

This opportunity will allow you to:

• Accelerate your career growth by working on state-of-the-art AI systems.
• Develop deep expertise in prompt engineering and model tuning.
• Hone your skills in building robust data pipelines and quality frameworks.

Microsoft'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.

Responsibilities:

• Design and implement new relevance metrics to measure and improve local search quality.
• Develop and optimize LLM/SLM labeling pipelines for high-throughput, consistent quality judgments.
• Engineer and fine-tune prompts for LLMs to enhance query understanding and classification accuracy.
• Apply modern LLM techniques such as retrieval-augmented generation for improved grounding and relevance.
• Build scalable workflows and dashboards for measurement, evaluation cycles, and quality checks.
• Analyze failure modes and improve prompt rubrics to reduce defect rates and enhance labeling consistency.
• Collaborate with cross-functional teams to integrate metrics and labeling systems into production environments.

Qualifications:

• 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.
• Relevant years customer-facing, project-delivery experience, professional services, and/or consulting experience.

Other Requirements:

• 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.

XML job scraping automation by YubHub

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.

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.

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.

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:

• Design, analyse, and interpret A/B online experiments to evaluate user engagement and generate actionable, trustworthy insights that inform product decisions.
• Perform hands-on analysis of large-scale telemetry data using advanced statistical methods, algorithms, and data tools to uncover meaningful patterns and trends.
• Develop and monitor key success metrics to measure and improve Bing customer satisfaction, engagement, and retention.
• Formulate data-driven strategies to understand correlations among critical Bing metrics and deliver clear, rigorous ship decisions.
• Effectively communicate analytical methodologies, data visualisations, and evidence-based recommendations across cross-functional teams to drive alignment and impact.

Qualifications:

• 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.

Preferred Qualifications:

• 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.

Experience with SQL-like query languages. Hands on experience in design & 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.

XML job scraping automation by YubHub

As a Bill of Material Systems Specialist at Honda's Auto Development Center, you will drive innovation in supply chain and production systems. You will leverage your expertise in BOM systems, data analytics, and digital tools to support critical projects and process improvements.

Responsibilities

• Develop and maintain BOM systems to support production and supply chain operations
• Analyze data to identify trends and opportunities for process improvements
• Collaborate with cross-functional teams to implement process changes and improvements
• Utilize digital tools to streamline processes and improve efficiency
• Support critical projects and initiatives to drive business growth

Requirements

• Bachelor's degree in Supply Chain Management, Operations Research, or related field
• 2+ years of experience in BOM systems, data analytics, or related field
• Strong analytical and problem-solving skills
• Excellent communication and collaboration skills
• Proficiency in digital tools and software

Benefits

• Competitive salary range: $72,000.00 - $108,000.00
• Comprehensive benefits package
• Opportunities for career growth and professional development
• Collaborative and dynamic work environment

How to Apply

If you are a motivated and detail-oriented individual with a passion for supply chain and production systems, please submit your application. We look forward to hearing from you!

XML job scraping automation by YubHub

Location

San Francisco

Employment Type

Full time

Department

Data Science

Compensation

• $440K – $490K • Offers Equity

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.

Benefits

• Medical, dental, and vision insurance for you and your family, with employer contributions to Health Savings Accounts

• Pre-tax accounts for Health FSA, Dependent Care FSA, and commuter expenses (parking and transit)

• 401(k) retirement plan with employer match

• 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)

• Paid time off: flexible PTO for exempt employees and up to 15 days annually for non-exempt employees

• 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)

• Mental health and wellness support

• Employer-paid basic life and disability coverage

• Annual learning and development stipend to fuel your professional growth

• Daily meals in our offices, and meal delivery credits as eligible

• Relocation support for eligible employees

• Additional taxable fringe benefits, such as charitable donation matching and wellness stipends, may also be provided.

About the Team

The Strategic Finance team at OpenAI plays a critical role in shaping the company’s long-term trajectory. We partner closely with Product, Engineering, and Go-to-Market teams to inform high-stakes decisions through rigorous data science and economic modeling.

As part of our expanding Data Science function, we’re building a best-in-class forecasting capability to drive real-time, data-driven decision-making across user growth, revenue, compute infrastructure, and more.

We are developing a scalable forecasting platform to help us understand and anticipate business dynamics in an increasingly complex, usage-based world. Our models are foundational to planning, pricing, operational efficiency, and growth strategy — supporting key investment decisions and unlocking OpenAI’s full potential.

About the Role

We’re looking for a hands-on technical leader to build and lead a small but mighty team of applied data scientists and ML engineers to develop forecasting capabilities and platforms from the ground up.

Your team will be responsible for building and scaling robust, interpretable, and production-ready forecasting systems. These models will power critical business decisions by predicting core metrics such as DAU/WAU, revenue, compute consumption, and profitability.

You will work closely with Strategic Finance leaders to integrate these scalable forecasting capabilities into their operational rhythms and collaborate with the Growth team to forecast key KPIs.

This is a highly cross-functional role that requires technical excellence, strong product intuition, and business acumen. You’ll collaborate with various partners to operationalize forecasting insights, influence company-wide strategy, and build foundational forecasting capabilities at OpenAI.

Responsibilities

• Build and manage a world-class team of applied data scientists and ML engineers to develop forecasting platforms at scale.

• Design and own the roadmap for the forecasting platform in partnership with cross-functional stakeholders.

• Collaborate closely with Strategic Finance teams to ensure forecasts are well integrated into planning processes, and executive decision-making.

• Work closely with cross-functional partners to help them adopt scientific, automated forecasting solutions.

• Own the end-to-end modeling lifecycle, including scoping, feature engineering, model development and prototyping, experimentation, deployment, monitoring, and explainability.

• Research and evaluate emerging tools and techniques in the forecasting space.

• Translate technical outputs into business-aligned recommendations and decision frameworks.

Requirements

• Extensive experience building production-ready models for time series applications.

• Proven track record of building adjustable and explainable forecast models for multiple planning cycles.

• 10+ years of applied data science & engineering experience, with deep hands-on expertise in forecasting and predictive modeling.

• Demonstrated experience with model monitoring, debugging, and long-term maintenance in production environments.

• Excellent communication and storytelling skills — able to simplify complexity and influence executive stakeholders.

• Team leadership experience with a track record of building high-performing, engaged teams.

• An advanced degree (MS or PhD) in a quantitative field (e.g., Statistics, Computer Science, Economics, Operations Research).

• A self-directed, intellectually curious mindset and comfort leading ambiguous projects from 0→1.

• The ability to thrive in a dynamic environment — flexible, resourceful, and willing to do what it takes

XML job scraping automation by YubHub

San Francisco

Employment Type

Full time

Department

Data Science

Compensation

• $347K – $490K • Offers Equity

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.

• Medical, dental, and vision insurance for you and your family, with employer contributions to Health Savings Accounts

• Pre-tax accounts for Health FSA, Dependent Care FSA, and commuter expenses (parking and transit)

• 401(k) retirement plan with employer match

• 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)

• Paid time off: flexible PTO for exempt employees and up to 15 days annually for non-exempt employees

• 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)

• Mental health and wellness support

• Employer-paid basic life and disability coverage

• Annual learning and development stipend to fuel your professional growth

• Daily meals in our offices, and meal delivery credits as eligible

• Relocation support for eligible employees

• Additional taxable fringe benefits, such as charitable donation matching and wellness stipends, may also be provided.

More details about our benefits are available to candidates during the hiring process.

This role is at-will and OpenAI reserves the right to modify base pay and other compensation components at any time based on individual performance, team or company results, or market conditions.

About the Team

The Strategic Finance team at OpenAI plays a critical role in shaping the company’s long-term trajectory. We partner closely with Product, Engineering, and Go-to-Market teams to inform high-stakes decisions through rigorous data science and economic modeling.

As part of our expanding Data Science function, we’re building a best-in-class forecasting capability to drive real-time, data-driven decision-making across user growth, revenue, compute infrastructure, and more.

We are developing a scalable forecasting platform to help us understand and anticipate business dynamics in an increasingly complex, usage-based world. Our models are foundational to planning, pricing, operational efficiency, and growth strategy — supporting key investment decisions and unlocking OpenAI’s full potential.

About the Role

We’re looking for a hands-on technical leader to build and lead a small but mighty team of applied data scientists and ML engineers to develop forecasting capabilities and platforms from the ground up.

Your team will be responsible for building and scaling robust, interpretable, and production-ready forecasting systems. These models will power critical business decisions by predicting core metrics such as DAU/WAU, revenue, compute consumption, and profitability.

You will work closely with Strategic Finance leaders to integrate these scalable forecasting capabilities into their operational rhythms and collaborate with the Growth team to forecast key KPIs.

This is a highly cross-functional role that requires technical excellence, strong product intuition, and business acumen. You’ll collaborate with various partners to operationalize forecasting insights, influence company-wide strategy, and build foundational forecasting capabilities at OpenAI.

This role is based in San Francisco, CA. We follow a hybrid work model of three days in the office per week and offer relocation assistance to new employees.

In this role, you will:

• Build and manage a world-class team of applied data scientists and ML engineers to develop forecasting platforms at scale.
• Design and own the roadmap for the forecasting platform in partnership with cross-functional stakeholders.
• Collaborate closely with Strategic Finance teams to ensure forecasts are well integrated into planning processes, and executive decision-making.
• Work closely with cross-functional partners to help them adopt scientific, automated forecasting solutions.
• Own the end-to-end modeling lifecycle, including scoping, feature engineering, model development and prototyping, experimentation, deployment, monitoring, and explainability.
• Research and evaluate emerging tools and techniques in the forecasting space.
• Translate technical outputs into business-aligned recommendations and decision frameworks.

You might thrive in this role if you have:

• Extensive experience building production-ready models for time series applications.
• Proven track record of building adjustable and explainable forecast models for multiple planning cycles.
• 10+ years of applied data science & engineering experience, with deep hands-on expertise in forecasting and predictive modeling.
• Demonstrated experience with model monitoring, debugging, and long-term maintenance in production environments.
• Excellent communication and storytelling skills — able to simplify complexity and influence executive stakeholders.
• Team leadership experience with a track record of building high-performing, engaged teams.
• An advanced degree (MS or PhD) in a quantitative field (e.g., Statistics, Computer Science, Economics, Operations Research).
• A self-directed, intellectually curious mindset and comfort leading ambiguous projects from 0→1.
• The ability to thrive in a dynamic environment — flexible, resourceful, and willing to do what it

XML job scraping automation by YubHub

San Mateo, CA, United States Data Science & Analytics ID: 5750

Every day, tens of millions of people come to Roblox to explore, create, play, learn, and connect with friends in 3D immersive digital experiences– all created by our global community of developers and creators.

At Roblox, we’re building the tools and platform that empower our community to bring any experience that they can imagine to life. Our vision is to reimagine the way people come together, from anywhere in the world, and on any device.

A career at Roblox means you’ll be working to shape the future of human interaction, solving unique technical challenges at scale, and helping to create safer, more civil shared experiences for everyone.

The Data Science & Analytics organization's mission is to increase our speed, frequency and acumen of making decisions at scale by instilling a data-influenced approach to building products. We cover a wide area of the data spectrum including analytical data engineering, product analytics, causal inference, economics, statistical modeling and machine learning. Aligned and partnering with product verticals, we use this extensive toolbelt to discover new opportunities and unmet use cases, influence and shape the product roadmap and prioritization, build data products and measure impact on our community of players and developers.

This is a temporary, part-time position requiring no more than 20 hours per week _for a 3-month duration, with possibility to extend._

Teams Hiring for this role:

• Foundation AI: Our AI evaluation team focuses on generating high-quality models and consistently improving our evaluation models.
• Safety: Managing account relationships and the real-time morphing of linguistic mapping.
• Economy: Drive creator success and growth by exploring marketplace structure and pricing.

You Will:

• Collaborate with data scientists and engineers to research and develop advanced data analytics, causal inference, experiment design and machine learning solutions to power the business and product innovations.
• Conduct in-depth research to address complex data-related challenges.
• Work on projects that have a real impact on our products, services, and business strategy.
• Apply your work to expedite product innovations, including in-experience experiments, friend recommendations, and dynamic resource allocation for experience servers
• Present your findings and recommendations to both technical and non-technical stakeholders.

You Have:

• Possessing or pursuing a PhD degree in a quantitative field such as Statistics, Applied Math, Computer Science, Economics, or Computational Social Science, Operations Research, Computer Engineering, Electrical Engineering.
• At least 1 year of experience doing causal inference or machine learning or experiment design via research or prior internship.
• Proficiency in one or more programming languages (e.g., SQL, Python or R)
• Proficiency in big data query/processing languages and tools such as SQL, Hive, Spark, or Airflow.
• Passion for applying scientific rigor to advance dynamic consumer products.
• Experience in developing production solutions is a plus.
• Experience with ML modeling

You may redact age, date of birth, and dates of attendance/graduation from your resume if you prefer.

For roles that are based at our headquarters in San Mateo, CA: The starting base pay for this position is as shown below. The actual base pay is dependent upon a variety of job-related factors such as professional background, training, work experience, location, business needs and market demand. Therefore, in some circumstances, the actual hourly rate could fall outside of this expected range. This pay range is subject to change and may be modified in the future. _Please note that not all benefits shown on this page are applicable to internship opportunities._

Hourly Pay Range

$64—$64 USD

Roles that are based in an office are onsite Tuesday, Wednesday, and Thursday, with optional presence on Monday and Friday (unless otherwise noted).

XML job scraping automation by YubHub

Microsoft AI are looking for a talented Principal Data Scientist at their Mountain View office. This role sits at the heart of strategic decision-making, turning market data into actionable insights for a company that's revolutionising AI-powered web search. You'll work directly with leadership to shape the company's direction in the online experimentation and search markets.

About the Role

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.

Accountabilities

• 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.
• 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.

The Candidate we're looking for

Experience:

• 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.

Technical skills:

• Experience with SQL-like query languages
• Hands on experience in design & problem-solving skills with one or more programming languages, such as Python, Java, C# or C++

Personal attributes:

• Ability to work independently, influence others, and solid communication and collaboration skills.

Benefits

• Competitive salary
• Comprehensive benefits package
• Opportunities for professional growth and development
• Collaborative and dynamic work environment
• Recognition and rewards for outstanding performance

XML job scraping automation by YubHub

Microsoft AI are looking for a talented Principal Data Scientist at their Redmond office. This role sits at the heart of strategic decision-making, turning market data into actionable insights for a company that's revolutionising AI-powered web search. You'll work directly with leadership to shape the company's direction in the online experimentation and AI experiences markets.

About the Role

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.

Accountabilities

• 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.
• 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.

The Candidate we're looking for

Experience:

• 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.

Technical skills:

• Experience with SQL-like query languages
• Hands on experience in design & problem-solving skills with one or more programming languages, such as Python, Java, C# or C++

Personal attributes:

• Ability to work independently, influence others, and solid communication and collaboration skills.

Benefits

• Competitive salary
• Comprehensive benefits package
• Opportunities for professional growth and development
• Collaborative and dynamic work environment
• Recognition and rewards for outstanding performance

XML job scraping automation by YubHub

You'll be responsible for supporting the production planning team in the development and implementation of production plans for new vehicle projects. This will involve working closely with cross-functional teams to ensure that production plans are aligned with business objectives and that all necessary resources are in place to meet production targets.

• Develop and maintain production plans for new vehicle projects, including scheduling, resource allocation, and capacity planning
• Collaborate with production planning team members to ensure that production plans are aligned with business objectives and that all necessary resources are in place to meet production targets
• Work closely with cross-functional teams, including engineering, procurement, and logistics, to ensure that production plans are aligned with business objectives and that all necessary resources are in place to meet production targets
• Analyze production data and provide insights to inform production planning decisions

What you need

To succeed in this role, you'll need a strong understanding of production planning principles and practices, as well as excellent analytical and problem-solving skills.

• Bachelor's degree in a relevant field, such as industrial engineering, operations research, or supply chain management
• 1-2 years of experience in production planning or a related field
• Strong understanding of production planning principles and practices
• Excellent analytical and problem-solving skills
• Ability to work effectively in a team environment
• Strong communication and interpersonal skills

Why this matters

This role is critical to the success of our production planning team and will play a key role in ensuring that we meet our production targets and deliver high-quality products to our customers. As a member of our team, you'll have the opportunity to work on exciting projects, develop your skills and knowledge, and contribute to the success of our organization.

XML job scraping automation by YubHub