The ideal candidate will have a high school diploma or GED, working knowledge of Microsoft Office applications, and the ability to operate independently. Experience with operating a powered industrial truck (fork truck) is a plus.

We offer a competitive hourly wage of $17.50, up to a 5% yearly bonus, and a comprehensive benefits package, including 120 hours of vacation, 128 hours of holiday time, and full medical, dental, and vision coverage.

If you're looking for a challenging and rewarding role in a dynamic organization, we encourage you to apply.

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The ideal candidate will have a high school diploma or General Educational Development (GED), demonstrate working knowledge of Microsoft (MS) Office applications, and be able to operate independently. Previous experience in a similar role is preferred, but not required.

As a Material Handler at Bayer, you will have the opportunity to work in a team environment, support strong attention to detail, and quickly learn new Information Technology (IT) systems and tools.

We offer a competitive hourly wage of $17.50 per hour, with additional compensation possible through a bonus or incentive program. Our benefits package includes health care, vision, dental, retirement, PTO, sick leave, and more.

If you're looking for a challenging and rewarding role in a dynamic organization, we encourage you to apply now.

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Key Responsibilities:

• Develop and implement system test solutions for complex electromechanical assemblies and combination products
• Stay ahead of emerging technologies and methodologies to enhance our manufacturing capabilities
• Review and analyze system specifications
• Spearhead the development of next-generation test equipment fixtures and processes
• Collaborate with cross-functional teams, external partners, and manufacturing sites to deliver projects on time and within budget
• Mentor junior engineers and promote Design for Excellence (DfX) initiatives
• Create and maintain comprehensive technical documentation, ensuring compliance with safety, quality, and regulatory standards

Requirements:

• Minimum of a Bachelor's Degree or an equivalent combination of education and experience
• Industry experience in the medical device sector (or other heavily regulated industry)
• Knowledge of best practices in software development lifecycle with proven ability in multiple languages
• Familiarity with MCAD and ECAD tools
• Proficient in statistical analysis and the use of statistical tools to interpret data, identify trends, and implement solutions that enhance accuracy and efficiency in systems testing
• Proven track record of leading and mentoring teams

Preferred Qualifications:

• At least 4 years of relevant industry experience in the medical device sector (or other heavily regulated industry)
• Experience developing dashboards in an informatics tool such as Power BI or Tableau

This position will be available for application until at least 4/27/2026. Employees can expect to be paid a salary between $112,400.00 - $168,600.00. Additional compensation may include a bonus or commission (if relevant). Additional benefits include health care, vision, dental, retirement, PTO, sick leave, etc.

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The role requires combining client relationship management with strong risk assessment and management capabilities to ensure the required credit quality and requisite returns on risk.

Key responsibilities include:

• Maintaining HSBC internal control standards, including timely implementation of internal and external audit points together with any issues raised by external regulators

• Originating target market clients focused on investment AUM, lending, and Advisory services, collaborating with US and LATAM network, as well as developing self-sourced prospects and referral sources in Mexico

• Growing revenues across allocated portfolio and originating new revenue streams, increasing HSBC's share of client wallet, involving product specialists to ensure product capabilities are in line with UHNW and HNW client requirements

• Establishing and maintaining networks for cooperation with other HSBC businesses to support the creation of solutions to customer needs that span geographical/product boundaries and regulatory environments

You will likely have the following qualifications to succeed in this role:

• Familiarity in working with clients and prospects who are high-potential HNW/UHNW clients

• Proven track record in asset gathering, asset growth, and revenue generation

• Highly developed communication skills for use in direct client contact and problem-solving

• Excellent understanding of financial markets and products

• Ability to provide strong financial and statistical analysis

• Attention to detail and the ability to think creatively to solve problems

• Series 7 and 66 licenses required

• Bachelor's Degree required

• Fluent in Spanish and English

As an HSBC employee, you will have access to tailored professional development opportunities to ensure you have the right skills for today and tomorrow. We offer a competitive pay and benefits package, including a robust Wellness Hub, all in a welcoming and inclusive work environment.

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As a Research Scientist/Engineer focused on honesty within the Finetuning Alignment team, you'll spearhead the development of techniques to minimize hallucinations and enhance truthfulness in language models.

Your work will focus on creating robust systems that are accurate and reflect their true levels of confidence across all domains, and that work to avoid being deceptive or misleading.

Your work will be critical for ensuring our models maintain high standards of accuracy and honesty across diverse domains.

Responsibilities

• Design and implement novel data curation pipelines to identify, verify, and filter training data for accuracy given the model’s knowledge

• Develop specialized classifiers to detect potential hallucinations or miscalibrated claims made by the model

• Create and maintain comprehensive honesty benchmarks and evaluation frameworks

• Implement techniques to ground model outputs in verified information, such as search and retrieval-augmented generation (RAG) systems

• Design and deploy human feedback collection specifically for identifying and correcting miscalibrated responses

• Design and implement prompting pipelines to generate data that improves model accuracy and honesty

• Develop and test novel RL environments that reward truthful outputs and penalize fabricated claims

• Create tools to help human evaluators efficiently assess model outputs for accuracy

Requirements

• Have an MS/PhD in Computer Science, ML, or related field

• Possess strong programming skills in Python

• Have industry experience with language model finetuning and classifier training

• Show proficiency in experimental design and statistical analysis for measuring improvements in calibration and accuracy

• Care about AI safety and the accuracy and honesty of both current and future AI systems

• Have experience in data science or the creation and curation of datasets for finetuning LLMs

• An understanding of various metrics of uncertainty, calibration, and truthfulness in model outputs

Preferred qualifications

• Published work on hallucination prevention, factual grounding, or knowledge integration in language models

• Experience with fact-grounding techniques

• Background in developing confidence estimation or calibration methods for ML models

• A track record of creating and maintaining factual knowledge bases

• Familiarity with RLHF specifically applied to improving model truthfulness

• Worked with crowd-sourcing platforms and human feedback collection systems

• Experience developing evaluations of model accuracy or hallucinations

Benefits

• Competitive compensation and benefits

• Optional equity donation matching

• Generous vacation and parental leave

• Flexible working hours

• Lovely office space in which to collaborate with colleagues

Visa sponsorship

We do sponsor visas! However, we aren'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.

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Reporting to the Vice President, Enterprise Data, you'll partner closely with senior leaders to improve how teams make decisions, measure performance, and drive outcomes, with a focus on shared views of usage and consumption models and major product launches.

You'll oversee two critical functions: Marketing Analytics (including demand generation, lifecycle marketing, brand, web, developer relations, localization, monetization, and campaign and event effectiveness) and Product Data Insights (including DevOps, Security, Platforms, AI products, new usage and consumption models, product adoption, feature usage, and customer behaviour analysis).

Key responsibilities include:

Defining and executing a unified analytics strategy across Marketing and Product, including shared metrics, measurement frameworks, and dashboards that serve as a single source of truth and connect marketing investment to product adoption, usage, and customer outcomes.

Building clear operating rhythms and ways of working that close historical gaps and help Marketing and Product make consistent, data-informed decisions.

Partnering with Marketing and Product leadership, including the Chief Product & Marketing Officer and other senior stakeholders, to provide actionable insights and executive-ready recommendations that shape go-to-market plans, product launches, roadmap prioritisation, and user experience improvements.

Solving complex analytics problems across both functions, including attribution modelling, lead scoring optimisation, campaign and event effectiveness, product adoption and feature usage analysis, and analytics for AI-powered features (including instrumentation, usage, and cost drivers).

Building and maintaining forecasting and scenario modelling frameworks in partnership with Finance, Product, and go-to-market leaders, tying pipeline, recurring revenue, and usage or consumption models to planning and investment decisions.

Establishing and scaling an experimentation programme across Marketing and Product, setting standards for hypothesis design, test methodology, instrumentation requirements, and clear readouts that translate results into decisions.

Building strong partnerships with data engineering, engineering, and legal, privacy, and security teams to translate business questions into technical requirements, prioritise telemetry and data model work, and improve reliability, quality, accessibility, and compliance in the analytics stack.

Hiring, mentoring, and developing leaders and team members, raising the bar for strategic thinking, stakeholder partnership, and end-to-end ownership across the analytics organisation.

Requirements include:

Strategic analytics leadership across both marketing analytics and product analytics, ideally in B2B SaaS or other high-growth technology environments.

Experience building, leading, and developing multi-layer analytics teams (including hiring, managing managers, and coaching leaders).

Ability to define and operationalise end-to-end measurement frameworks across Marketing and Product, including shared KPIs and clear metric definitions.

Strong analytical and technical skills, including SQL; statistical analysis and experimentation (A/B and multivariate testing); forecasting and scenario modelling; and advanced analytics techniques.

Experience with data visualisation and BI tools (Tableau or similar), with a track record of building executive-ready reporting and narratives for senior leaders.

Proven partnership with Engineering and Data Engineering to translate business needs into telemetry, data models, and analytics requirements, and to improve reliability and delivery across the analytics stack.

Experience collaborating with Legal, Privacy, and Security partners to design compliant telemetry and data-collection approaches that respect regulations and customer expectations.

Ability to influence senior leaders through clear communication and actionable recommendations, and to work effectively in a fully remote, asynchronous environment while adopting GitLab's values and ways of working.

The base salary range for this role's listed level is currently $184,400-$314,400 USD for residents of the United States only.

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The individual in this role will focus on in-depth data analysis, metric definition, benchmark creation, experimentation, and synthesis to high-level insights for prioritization.

Responsibilities:

• Conduct advanced data analysis to extract actionable insights that inform strategic decisions.
• Collaborate closely with business teams, providing data-driven insights to support strategic decisions.
• Analyze broad data to understand the impact of incentives on bookings, attach rate, revenue, profitability, occupancy, rebooking rate, churn, and other key metrics.
• Define new metrics and identify leading indicators of key business outcomes.
• Build dashboards to track key performance metrics across markets and customer segments to establish benchmarks.
• Conduct A/B tests to improve business performance and maximize incrementality.
• Collaborate with cross-functional teams, including Strategic Finance, Data and Analytical Engineering, and Data Science, to align strategies and leverage synergies.

Your Expertise:

• 10+ years of industry experience with a degree (Masters or PhD is a plus) in a quantitative field (e.g., Statistics, Econometrics, Computer Science, Engineering, Mathematics, Data Science, Operations Research).
• Prior experience in advanced analytics or business data science within a marketplace or business strategy setting.
• Strong expertise in at least one programming language (Python or R) and SQL.
• Experience with AI-assisted analytics (Claude, ChatGPT, etc).
• Deep understanding of econometric and statistical analysis, and experience in applying these skills to derive insights from broad data sets.
• Exceptional business acumen, strategic thinking skills, and the ability to make informed judgments.
• Excellent communication skills, capable of engaging with a variety of stakeholders and conveying complex concepts in an accessible manner.
• Proven stakeholder management skills, with the ability to collaborate and influence across functions.
• An agile, growth-minded approach, demonstrated through a history of driving projects from ideation to impact.

Your Location:

This position is US - Remote Eligible. The role may include occasional work at an Airbnb office or attendance at offsites, as agreed to with your manager.

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You will join a team of top-tier data scientists and become an integral part of the product organisation, helping to scale this new business.

Joining on the ground floor of this startup team, you'll partner directly with the Head of Data Science and Product, Engineering and Design leadership to shape the product roadmap, foster a top-tier, data-informed culture, and drive real AI/ML impact and execution along the way!

Responsibilities

• Manage and scale a high performing team of data scientists

• Coach and mentor data scientists of varying experiences to ensure their continued growth

• Plan, execute, and deliver a portfolio of mission-critical data science projects for Dash Experience, and provide technical leadership in a fast-paced environment

• Leverage data-driven insights to proactively identify most impactful opportunities, and directly influence product roadmaps and strategies

• Translate complex data insights into implications and recommendations for the business via excellent communication skills, both verbal and written

• Work with cross-functional teams (including Product, Engineering, Design, User Research, and senior executives) to rapidly execute and iterate

• Partner with Product Engineers and Data Engineers to build the reliable, efficient, and scalable data foundations, tools, and processes to drive our AI/ML capabilities' long-term growth

• Identify what matters most and prioritise ruthlessly

Requirements

• Bachelor's or above in quantitative discipline: Statistics, Applied Mathematics, Economics, Computer Science, Engineering, or related field

• 10+ years experience of leveraging data-driven analysis to influence product roadmap and business decision, preferably in a tech company

• 3+ years of experience directly managing data scientists or product analysts

• Proven track record of managing a portfolio of Data Science projects that improve user experience and drive measurable business impact

• Deep understanding of statistical analysis, experimentation design, and common analytical techniques

• Experience using data to inform product and business decisions that led to measurable outcomes

• Exceptional verbal and written communication skills

Preferred Qualifications

• Experience in startups or building 0→1 products

• Expertise in using data to inform AI/ML product development

• Background in SaaS product

Compensation

Canada Pay Range $187,900-$254,100 CAD

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How often do you get the opportunity to be on the ground floor of a big and important mission? As a Senior Data Scientist for Dropbox's AI-first journey, you will join a team of top-tier data scientists and become an integral part of the product organisation, helping to scale this new business.

You will partner directly with Data Science, Product, Engineering and Design leadership to shape the product roadmap, foster a top-tier, data-informed culture, and drive real AI/ML impact and execution along the way!

Responsibilities

• Partner with Product Engineers and Data Engineers to build the reliable, efficient, and scalable data foundations, tools, and processes to drive our AI/ML capabilities' long-term growth
• Leverage data-driven insights to proactively identify most impactful opportunities, and directly influence product roadmaps and strategies
• Perform exploratory and deep-dive analysis to understand user workflows and engagement patterns on AI features, propose hypothesis, and design & execute experiments with great rigor and efficient data techniques
• Translate complex data insights into implications and recommendations for the business via excellent communication skills, both verbal and written
• Identify what matters most and prioritise ruthlessly for the area you will own
• Contribute to a culture of strong technical ownership, partner with DS leadership to keep evolving DS working model and elevate DS impact
• Work with cross-functional teams (including Product, Engineering, Design, User Research, and senior executives) to rapidly execute and iterate

Requirements

• Bachelor's or above in quantitative discipline: Statistics, Applied Mathematics, Economics, Computer Science, Engineering, or related field
• 7+ years experience of leveraging data-driven analysis to influence product roadmap and business decision, preferably in a tech company
• Proven track record of being able to work independently, drive measurable business impact, and proactively engage with business stakeholders with minimal direction
• Proficiency in SQL, Python or other programming/scripting languages
• Deep understanding of statistical analysis, experimentation design, and common analytical techniques like regression, decision trees
• Ability to provide data insights and recommendations for 0→1 product even when sample size is small
• Strong verbal and written communication skills

Preferred Qualifications

• Experience in startups or building 0→1 products
• Expertise in using data to inform AI/ML product development
• Background in SaaS product

Compensation

US Zone 2: $173,700-$234,900 USD US Zone 3: $154,400-$208,800 USD

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Your responsibilities will include:

• Analyzing data to uncover patterns, insights, and trends, as well as answering complex legal and comms based Safety questions for external communication
• Leveraging analysis to design operational response solutions in the Safety landscape
• Writing retros of Safety incidents with a focus on guardrail solutions and clear runbooks
• Iterating, improving, and socializing reporting to the needs of an emergent safety landscape across teams and efforts with a focus on stable or self-help solutions
• Delivering long-term project work in the Safety operations landscape with some oversight
• Documenting , in detail , your work, its impact, and the guardrails present in your design
• Assisting in developing scalable, clean data infrastructure
• Partnering with teams across Safety to increase the impact of your work

To be successful in this role, you will need to have:

• Fluent SQL, BigQuery dialect preferred
• Experience updating data architecture in version control systems such as Git
• Data Reporting experience, with an understanding of new feature design and guardrails
• Statistical analysis training
• Can determine path for code/data review with limited direction
• Maintain high levels of confidentiality and accuracy while performing legal requests
• Beyond just fielding requests, able to discuss data availability and limitations to help craft a request with a stakeholder
• Excellent written communication and documentation skills
• Ability to foster relationships and communicate complex concepts to stakeholders
• Ability to prioritize tasks and work independently, but oversight and coaching is expected
• Familiarity with Claude Code and leveraging AI tools to expand impact

The ideal candidate will be able to demonstrate a strong understanding of data analysis and visualization, as well as excellent communication and collaboration skills. If you are passionate about working with data and want to make a meaningful impact, we encourage you to apply.

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To be successful in this role, you will need to have 3+ years of experience applying ML to real-world problems, preferably in a growth or user acquisition context. You will need to have excellent communication skills and the ability to work effectively in cross-functional teams. You will need to have strong problem-solving skills and the ability to translate business requirements into technical solutions. You will need to have strong programming skills in Python and experience with PyTorch. You will need to have proficiency in data processing and analysis using tools like SQL, Spark, or Hadoop. You will need to have experience with recommendation systems, user modeling, or personalization algorithms. You will need to have familiarity with statistical analysis. You will need to have experience using AI coding assistants and agentic tools as a force-multiplier, and equally comfortable solving problems from first principles when those tools aren’t available. You will need to have a Bachelor’s/Master’s degree in a relevant field or equivalent experience.

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Joining on the ground floor of this startup team, you'll partner directly with Data Science, Product, Engineering and Design leadership to shape the product roadmap, foster a top-tier, data-informed culture, and drive real AI/ML impact and execution along the way!

Responsibilities

• Partner with Product Engineers and Data Engineers to build the reliable, efficient, and scalable data foundations, tools, and processes to drive our AI/ML capabilities' long-term growth
• Leverage data-driven insights to proactively identify most impactful opportunities, and directly influence product roadmaps and strategies
• Perform exploratory and deep-dive analysis to understand user workflows and engagement patterns on AI features, propose hypothesis, and design & execute experiments with great rigor and efficient data techniques
• Translate complex data insights into implications and recommendations for the business via excellent communication skills, both verbal and written
• Identify what matters most and prioritise ruthlessly for the area you will own
• Contribute to a culture of strong technical ownership, partner with DS leadership to keep evolving DS working model and elevate DS impact
• Work with cross-functional teams (including Product, Engineering, Design, User Research, and senior executives) to rapidly execute and iterate

Requirements

• Bachelor's or above in quantitative discipline: Statistics, Applied Mathematics, Economics, Computer Science, Engineering, or related field
• 7+ years experience of leveraging data-driven analysis to influence product roadmap and business decision, preferably in a tech company
• Proven track record of being able to work independently, drive measurable business impact, and proactively engage with business stakeholders with minimal direction
• Proficiency in SQL, Python or other programming/scripting languages
• Deep understanding of statistical analysis, experimentation design, and common analytical techniques like regression, decision trees
• Ability to provide data insights and recommendations for 0→1 product even when sample size is small
• Strong verbal and written communication skills

Preferred Qualifications

• Experience in startups or building 0→1 products
• Expertise in using data to inform AI/ML product development
• Background in SaaS product

Compensation

Canada Pay Range $162,400-$219,600 CAD

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Responsibilities:

• Lead projects from concept, design, implementation, to rollout, ensuring the highest quality and performance.
• Identify opportunities to enhance ranking capabilities by diving deep into our platform and understanding the needs of our customers.
• Design and develop applied machine learning models for modeled personalization, game taxonomy, and more, from ideation to production deployment.
• Collaborate with data scientists, product managers, and backend software engineers.
• Mentor junior team members, share knowledge, and contribute to the technical growth of the team.
• Provide guidance on machine learning best practices and methodologies.
• Conduct A/B tests and experiments to iterate and fine-tune algorithms and models.
• Stay updated on state-of-the-art algorithmic techniques and recognize promising innovations, adapting them to Reddit's unique platform and community.

Minimum Qualifications:

• 7+ years of experience in a relevant industry or academic background, preferably in a quantitative/modeling or highly scalable computing environment.
• Prior experience with personalized feed ranking.
• Proven track record of delivering complex machine learning projects from conception to deployment, preferably in real-world applications.
• Ability to lead and mentor machine learning engineers or data scientists.
• Strong communication skills to collaborate effectively with cross-functional teams and stakeholders.
• Demonstrated ability to innovate and stay updated with the latest advancements in machine learning and AI.

Preferred Qualifications:

• Experience of orchestrating complicated data pipelines and system engineering on large-scale datasets.
• Proficiency with programming languages and statistical analysis.
• Prior experience with Sequence Modeling, Reinforcement Learning, or Transformer Architecture.
• Experience in Bayesian methodology and experimentation.

Benefits:

• Comprehensive Healthcare Benefits and Income Replacement Programs.
• 401k with Employer Match.
• Family Planning Support.
• Gender-Affirming Care.
• Mental Health & Coaching Benefits.
• Flexible Vacation & Paid Volunteer Time Off.
• Generous Paid Parental Leave.

Pay Transparency:

This job posting may span more than one career level. In addition to base salary, this job is eligible to receive equity in the form of restricted stock units, and depending on the position offered, it may also be eligible to receive a commission.

To provide greater transparency to candidates, we share base salary ranges for all US-based job postings regardless of state. We set standard base pay ranges for all roles based on function, level, and country location, benchmarked against similar stage growth companies.

Final offer amounts are determined by multiple factors including, skills, depth of work experience and relevant licenses/credentials, and may vary from the amounts listed below.

The base salary range for this position is $230,000-$322,000 USD.

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In this pivotal leadership role, you will define and implement the next generation of foundational data science solutions, leveraging expertise in statistics, econometrics, machine learning, and other quantitative methods to optimize Reddit's Ads marketplace.

As a thought leader, you will champion scientific rigor, causal inference, and economic modeling, while providing deep mentorship to the broader team.

Key responsibilities include:

• Defining the future of Ads Data Science and owning the design and long-term evolution of our core Ads Data Science solutions and infrastructure
• Identifying fundamental gaps and opportunities in our current systems and leading the strategic design and scientific roadmap for new solutions
• Taking end-to-end ownership of complex problem domains such as full funnel acceleration, advertiser lifetime value (LTV), and developing advanced predictive and causal frameworks
• Establishing scientific standards and defining best practices for large-scale statistical modeling, economic analysis, causal inference, offline model evaluation, and A/B experimentation

Requirements include:

• Demonstrated expertise in at least one of the following: ads marketplace understanding, auctioning/bidding, ads creative & format evaluation, measurement & experimentation at scale
• Master's or Ph.D. in Economics, Statistics, Computer Science, Operations Research, or a related quantitative discipline
• Advanced proficiency in statistical programming (Python or R) and SQL
• Experience with statistical analysis, economic modeling, foundational machine learning and/or optimization techniques
• Strong understanding of experimental design, causal inference, or A/B testing methodologies

Benefits include comprehensive healthcare benefits, income replacement programs, 401k with employer match, global benefit programs, family planning support, gender-affirming care, mental health & coaching benefits, flexible vacation & paid volunteer time off, and generous paid parental leave.

The base salary range for this position is $268,000-$365,100 USD.

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In this role, you will specialize in improving and optimizing our ads auction and pricing mechanism which will have a direct impact on upleveling the utility for both our advertiser and user values. You will also have the opportunity to work on other org-wide strategic initiatives such as supply optimization and ad relevance, where you will drive and execute on Reddit’s vision to transform Reddit into an advertising platform that shows the right ads to the right users at the right time in the right context.

As a Staff Machine Learning Engineer in the Ads Marketplace Quality team, you will be an industry technical leader with domain knowledge in ads marketplace dynamics, auction and pricing, you will research, formulate, and execute on our mission to build end-to-end algorithmic solutions and deliver values to all the three-sided participants to our marketplace.

Responsibilities:

• Lead and oversee the strategy development, quarterly planning and day-to-day execution of initiatives related to ads marketplace, auction and pricing.
• Proactively further our understanding of marketplace dynamics and develop algorithms to improve the efficiency and effectiveness of our ads marketplace, auction and pricing.
• Oversee end-to-end ML workflows,from data ingestion and feature engineering to model training, evaluation, and deployment,that optimizes the ads marketplace efficiency.
• Be a mentor, lead both junior and senior engineers in implementing technical designs and reviews. Fostering a culture of innovation, technical excellence, and knowledge sharing across the organization.
• Be a cross-functional advocate for the team, collaborate with cross-functional teams (e.g., product management, data science, PMM, Sales etc.) to innovate and build products.

Required Qualifications:

• 8+ years of experience with industry-level product development, with at least 5+ years focused on data-driven, marketplace-optimization problem space at scale.
• Strong knowledge of ads marketplace optimization. Demonstrated experience architecting ads marketplace design, improving and optimizing ads auction and pricing mechanisms.
• Solid understanding of large-scale data processing, distributed computing, and data infrastructure (e.g., Spark, Kafka, Beam, Flink).
• Proficiency in machine learning frameworks (e.g., TensorFlow, PyTorch) and libraries for feature engineering, model training, and inference.
• Proficiency with programming languages (Java, Python, Golang, C++, or similar) and statistical analysis.
• Proven technical leadership in cross-functional settings, driving architectural decisions and influencing stakeholders (product, data science, privacy, legal).
• Excellent communication, mentoring, and collaboration skills to align teams on a long-term vision for ads marketplace optimization.

Benefits:

• Comprehensive Healthcare Benefits
• 401k Matching
• Workspace benefits for your home office
• Personal & Professional development funds
• Family Planning Support
• Flexible Vacation (please use them!) & Reddit Global Wellness Days
• 4+ months paid Parental Leave
• Paid Volunteer time off

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You will join the Production organisation at Anduril, responsible for the end-to-end processes of procuring, manufacturing, and delivering hardware to customers. As a Business Operations Associate, you will be embedded in the operations of the business, working across Supply Chain, Manufacturing, Planning, and teams outside Production like Finance, Growth, HR, etc.

Key Responsibilities:

• Own operational projects end-to-end, from Definition, Solution, to Implementation.
• Work on operational problems involving the intersection of hardware and software systems.
• Work on strategic problems, providing structure to ambiguity and helping shepherd cross-functional groups of stakeholders towards decisions on strategic issues.
• Work deeply within data and systems, becoming intimately familiar with how our business systems (ERP, MRP, HRIS, etc.) function, and how to leverage data from them to create insights and analytics.
• Execute scrappy analyses on short-timelines to get answers quickly, while also owning more scalable solutions that will make Anduril successful in the long term.

Requirements:

• 2+ years of experience in management consulting, investment banking, internal operations, a business analyst role - or some other experience where you just had to figure out how to get stuff done.
• Self-driven and relentlessly proactive.
• Able to step into the gap to offer solutions yourself.
• An appetite to build clear frameworks to structure problems.
• Strong analytical aptitude.
• Comfortable communicating broadly and having a lot of eyes on your work.

Salary Range: $113,000-$149,000 USD

Benefits:

• Comprehensive medical, dental, and vision plans at little to no cost to you.
• Income Protection: Anduril covers life and disability insurance for all employees.
• Generous time off: Highly competitive PTO plans with a holiday hiatus in December.
• Family Planning & Parenting Support: Coverage for fertility treatments (e.g., IVF, preservation), adoption, and gestational carriers, along with resources to support you and your partner from planning to parenting.
• Mental Health Resources: Access free mental health resources 24/7, including therapy and life coaching.
• Professional Development: Annual reimbursement for professional development.
• Commuter Benefits: Company-funded commuter benefits based on your region.
• Relocation Assistance: Available depending on role eligibility.

Retirement Savings Plan:

• Traditional 401(k), Roth, and after-tax (mega backdoor Roth) options.

Protecting Yourself from Recruitment Scams:

• No Financial Requests: Anduril will never solicit payment or demand personal financial details (such as banking information).
• Be cautious of unsolicited job offers or requests for personal information.
• Verify the authenticity of any communication from Anduril by contacting the company directly.

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This role requires a deep understanding of product analytics, a strong technical skillset, and a forward-thinking mindset to leverage AI in your analysis.

Responsibilities:

• Design and build insightful and user-friendly dashboards and reports in Tableau to track key product metrics and performance indicators.
• Utilize Snowflake and dbt to build and maintain robust and scalable data models and pipelines for our analytics needs.
• Conduct in-depth product analysis to identify trends, patterns, and opportunities for product improvement and growth.
• Write complex SQL queries and use Python to perform advanced data analysis.
• Collaborate with product managers, engineers, and other stakeholders to understand their data needs and provide them with the insights they need to make informed decisions.
• Proactively identify and explore new ways to leverage AI and machine learning to enhance our analytical capabilities and unlock new insights from our data.
• Communicate your findings and recommendations effectively to both technical and non-technical audiences.

Qualifications:

• Proven experience as a Data Analyst or in a similar role, with a focus on product analytics.
• 3-5 years of experience.
• Expert-level proficiency in SQL.
• Strong experience with data visualization tools, particularly Tableau.
• Hands-on experience with cloud data warehouses like Snowflake and data transformation tools like dbt.
• Advanced analytics, data science, AI/ML experience and techniques are a plus.
• A strong analytical mindset with the ability to think critically and solve complex problems.
• A proactive and curious mindset with a strong desire to learn and experiment with new technologies, especially in the realm of AI.
• Excellent communication and collaboration skills.

Added Advantage:

• Experience with other BI tools like Looker.
• Experience with statistical analysis and machine learning.
• Familiarity with product analytics platforms like Amplitude or Mixpanel

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Responsibilities:

• Work with technical and business teams to develop robust insights, create data narratives and leverage Airbnb’s rich data to define metrics.
• Build advanced analytical capabilities and tools, passionate about solving complex problems with data; adding a new perspective to existing solutions and making business decisions based on careful and thoughtful analysis.
• Leverage Airbnb’s state-of-art machine learning infrastructure, and other central data science tools to build and collaborate with a strong team of engineers, product managers, designers and operation agents to achieve shared, cross-functional goals.
• Develop a deep understanding of how guests and hosts interact with our payments platform and how we can manage our risk while meeting our regulatory compliance requirements, through structured and unstructured data sources.

A Typical Day:

• Execute projects with regular direction; Set a roadmap for projects up to a quarter ahead providing constant updates to business stakeholders, analytics management and deliver against agreed timelines.
• Ensure the availability of data quality and data integrity for analysis and reporting, by blending external and internal data, working closely with global operations and India analytics functions.
• Perform data modeling for the various entities involved in Airbnb including customers, hosts, cases, agents, and others using modern data modeling tools and frameworks to provide the analytical foundation of Airbnb’s Advance Analytics positions.
• Execute ad-hoc reporting, data investigations, and root cause analysis into various operational areas including policy incubation, enforcement efficacy, prevalence, efficiency, agent tooling, agent staffing & optimization, and agent quality & efficiency to identify and solve for operational bottlenecks and inefficiencies.
• Devise business metric frameworks and optimization models to make optimal business decisions that support arguments for Airbnb’s product, operations and policy issues - Influence data-driven decisions across global sites and business verticals in day-to-day via business reviews, self-serve portal, planning scorecards, and impact analyses among others.
• Experiment with new Airbnb policy / product features to help deter and mitigate risk - Influence machine learning models in partnership with DS / Engg teams to automate policy enforcement decisions, while enqueueing the most complex cases for manual review by agents

Your Expertise:

• 6+ years of industry experience and an Advanced degree in Business Analytics or other (Masters or PhD is a plus) in a quantitative field (e.g., Statistics, Econometrics, Computer Science, Engineering, Mathematics, Data Science, Operations Research).
• Good communication and collaboration skills with the ability to work effectively with internal teams in a cross-cultural and cross-functional environment. Ability to conduct rigorous analysis and communicate conclusions to both technical and non-technical audiences
• Proven track record of delivering full stack data projects from inception to business impact.
• Advanced level proficiency in SQL/NoSQL, programming languages such as Python, R, SAS and Intermediate level knowledge of data foundations and databases like Presto, Hive, Teradata, Spark.
• Familiarity with EDA, hypothesis testing, significance testing, linear regression, logistic regression, SVM, ridge regression, lasso regression, random forest, basic concepts of NLP, KNN, K-Means, A/B testing, multivariate testing, and digital funnel testing.
• Beginner level understanding of statistical and machine learning techniques, Tableau or similar BI platform to develop reports and dashboards
• Have a positive and solution-oriented mindset with an ability to maintain confidentiality and objectivity.
• Exceptional problem-solving abilities, self-motivation and ability to work autonomously, strong organizational and time management skills, with the ability to manage multiple priorities and meet deadlines.
• Knowledge and experience in payments processes, systems and tools would be a plus - Knowledge and experience in risk/compliance processes and data needs would be a plus

Our Commitment To Inclusion & Belonging:

Airbnb is committed to working with the broadest talent pool possible. We believe diverse ideas foster innovation and engagement, and allow us to attract creatively-led people, and to develop the best products, services and solutions. All qualified individuals are encouraged to apply.

How We'll Take Care of You:

Our job titles may span more than one career level. The actual base pay is dependent upon many factors, such as: training, transferable skills, work experience, business needs and market demands. The base pay range shown below is annualized, is inclusive of allowances and is subject to change and may be modified in the future. This role may also be eligible for bonus or incentives, one or more equity programs, benefits, and Employee Travel Credits. India Annual Pay Range₹1,890,000-₹2,700,000 INR

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As a Data Scientist lead on the GeminiApp team, you will be instrumental in building a uniquely proactive and powerful assistant by ensuring our strategic decisions are grounded in data.

Responsibilities

• Partner with PM, engineering, and UX leadership to develop data-driven product strategies across various areas of GeminiApp

• Translate ambiguous questions into well-defined problems, design experiments, and analyze large complex datasets for insights

• Develop and implement novel, goal-oriented metrics

• Build and deploy statistical/ML models to understand our users, enhance product capabilities and personalize user experience

• Communicate findings & recommendations to stakeholders, including executives

• Champion data-driven culture by feeding user engagement insights back into models

• Collaborate with the GenAI team on model quality and feature adoption

• Act as a technical leader for a global team, guiding junior members on complex analyses and upholding best practices to ensure high-quality, impactful work

What We're Looking For

• A bias for action and a relentless drive to build something great

• Strong business acumen and a strategic mindset

• Deep technical expertise

• Exceptional communication and presentation skills

• A collaborative and influential partner

• A commitment to user trust and privacy

Why You'll Love Working Here

• Impact: You'll have a direct and meaningful impact on a product designed to empower billions of people

• Growth: We're a fast-growing team within Google, and you'll have the opportunity to evolve quickly to meet changing user needs

• Team & Culture: You'll work with a talented and passionate team of people who are excited about what they do and have fun doing it

Minimum qualifications

• Master's degree in Statistics, Data Science, Mathematics, Physics, Economics, Operations Research, Engineering, or a related quantitative field

• 10 years of work experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or 8 years of work experience with a PhD degree

Preferred qualifications

• Graduate degree in Statistics, Computer Science, Engineering or Mathematics

• Familiarity with modern Machine Learning and LLM techniques

• Strong organization and prioritization skills along with outstanding written and verbal communication skills

• Strong data science coding skills in Python, R, SQL or related languages

• Experience articulating business questions and using mathematical techniques to arrive at an answer using available data

• Experience translating analysis results into business recommendations

• Proven experience delivering bespoke analytics to senior stakeholders (problem scoping/definition, modeling, interpretation, presentation)

Salary

The US base salary range for this full-time position is between $248,000 USD - 349,000 USD + bonus + equity + benefits.

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As a Modeling & Simulation Engineer, you will be responsible for improving and adding to our sensor and communications model suite so that our operator training and internal engineering pipelines have a seamless translation from sim to real results.

Responsibilities

• Develop and enhance radar sensor models for use in simulation and evaluation of aeronautical vehicles.
• Translate theoretical models into efficient, reliable C++ implementations with a focus on numerical accuracy and performance.
• Validate models against real-world data and authoritative references, including field test data and calibration procedures.
• Collaborate with simulation and training application teams to ensure models integrate cleanly into operator-facing tools.
• Design automated validation and regression testing strategies for mathematical models to ensure fidelity across releases.
• Prototype and evaluate new modeling techniques (reduced-order models, uncertainty quantification, machine learning–based surrogates) to push the state of the art.
• Document assumptions, equations, and validation results so that both engineers and operators can trust model outputs.

Requirements

• BS or higher in Aerospace Engineering, Applied Math, Physics, or related field with 5+ years of aerospace modeling experience.
• C++ foundation with experience implementing numerical methods.
• Demonstrated experience with aerospace models such as: Radar sensors, Radio communications systems
• Experience validating simulations against real-world or experimental data.
• Ability to write clear documentation explaining assumptions, limitations, and expected behaviors of models.

Preferences

• 1+ years of experience working on pilot/operator training systems.
• Experience with Eigen or SciPy for model prototyping and validation.
• Familiarity with state estimation sensor models (GPS, IMU, Gyro, etc) for simulation environments.
• Demonstrated experience with payload sensor models including: Laser sensors, IR and optical cameras
• Knowledge of uncertainty quantification and statistical analysis methods.
• Experience with parallelization or GPU acceleration for compute-heavy models.
• Strong problem-solving mindset with a collaborative and detail-oriented approach.
• Familiarity with Python for test automation and data analysis pipelines.
• Passion for aerospace and autonomous vehicle systems.

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As a Modeling & Simulation Engineer, you will be responsible for improving and adding to our world and aeronautical models so that our operator training and internal engineering pipelines have a seamless translation from sim to real results.

Responsibilities

• Develop and enhance aeronautical physics models (aerodynamics, propulsion, environmental, structural, etc.) for use in simulation and evaluation.
• Translate theoretical models into efficient, reliable C++ implementations with a focus on numerical accuracy and performance.
• Validate models against real-world data and authoritative references, including field test data and calibration procedures.
• Collaborate with simulation and training application teams to ensure models integrate cleanly into operator-facing tools.
• Design automated validation and regression testing strategies for mathematical models to ensure fidelity across releases.
• Prototype and evaluate new modeling techniques (reduced-order models, uncertainty quantification, machine learning–based surrogates) to push the state of the art.
• Document assumptions, equations, and validation results so that both engineers and operators can trust model outputs.

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In this role, you'll develop and maintain robust quality systems aligned with AS9100 standards, lead root cause investigations, and implement effective corrective and preventive actions. You'll partner closely with engineering, manufacturing, and supplier teams to identify risks, improve process capability, and ensure consistent product quality.

As a Staff Quality Engineer, you'll play a key role in shaping quality strategy, mentoring team members, and influencing cross-functional decisions without direct authority. This is an opportunity to work hands-on with next-generation aerospace technology and contribute directly to the delivery of highly reliable autonomous systems that will define the future of aviation.

Responsibilities:

• Develop and maintain robust quality systems in alignment with AS9100 standards
• Lead root cause investigations and implement effective corrective and preventive actions
• Partner closely with engineering, manufacturing, and supplier teams to identify risks, improve process capability, and ensure consistent product quality
• Support new product introduction (NPI) efforts, establish control plans and inspection strategies, and use data-driven methods to monitor and improve manufacturing performance

Required qualifications:

• Bachelor's degree in Engineering or a related technical field (or equivalent practical experience)
• 5+ years of experience in Quality, Manufacturing, or Process Engineering roles
• Demonstrated experience leading root cause analysis and implementing effective corrective and preventive actions (RCA/CAPA)
• Strong knowledge of quality systems and standards (AS9100 or similar)
• Experience supporting new product introduction (NPI) and scaling production in a manufacturing environment
• Proficiency in statistical analysis and process control methods (SPC, capability analysis, etc.)

Preferred qualifications:

• Experience in aerospace, defense, or other high-reliability industries
• ASQ Certified Quality Engineer (CQE), Lean Six Sigma certification, or equivalent
• Knowledge of design for quality principles, including DFMEA, tolerance analysis, and design reviews
• Experience working with quality and manufacturing systems (QMS, MES, PLM) and data analysis tools
• Familiarity with advanced inspection or test methods (metrology, NDT, automated inspection, etc.)

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You will develop software infrastructure to streamline and automate these analyses to accelerate learning cycles. Finally, you will collaborate closely with researchers and engineers across Rigetti to monitor and improve fabrication yield, and improve the models and infrastructure used to predict processor performance from foundry metrology data.

Key responsibilities include designing and implementing industry-grade software infrastructure in Python to streamline feedback from measurement to the integrated circuit design team, identifying correlations between fabrication metrology data and processor performance through the analysis of empirical datasets, and utilizing techniques and best practices in statistical analysis and machine learning to accurately calibrate various processor design parameters.

Required qualifications include an undergraduate degree in Computer Science, Physics, Applied Physics, Electrical Engineering, or a related field, 6+ years of experience in data science and statistical analysis in a scientific field, and programming skills in Python for scientific applications.

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About Us: Mercury is a fintech company that provides banking services to entrepreneurs and businesses.

Job Description: We are looking for a Senior Manager to lead our BSA/AML & Sanctions Modeling and Analytics function. The successful candidate will own and drive enhancement of our financial crime (anti-money laundering and sanctions) detection models. This role will own transaction monitoring, sanctions screening, and customer risk scoring models,ensuring they are data-driven, well-governed, and defensible.

Responsibilities:

• Build the modeling and analytics function and take ownership of model documentation, tuning, and partner with engineering for model development.
• Develop and execute the modeling and analytics roadmap supporting the company’s Financial Crimes Compliance program.
• Partner with senior Compliance, Product, and Data leaders to translate regulatory requirements into effective analytical frameworks.
• Champion analytical excellence, model governance, and innovation in AML and Sanctions detection approaches.
• Design, implement, and maintain statistical and machine learning models for transaction monitoring, sanctions screening, customer risk scoring, and alert optimization.
• Ensure models and rules have appropriate documentation in line with Mercury’s Model Risk Management framework, draft new documentation for existing models as needed.
• Evaluate and tune existing detection models and rules to reduce false positives while maintaining regulatory rigor.
• Develop data-driven methods to identify new typologies, emerging risks, and evolving financial crime trends.
• Partner with Model Risk Management to support validation and performance monitoring of models to ensure compliance with internal and regulatory standards.

Requirements:

• 5-8 years of experience leading modelling and analytics functions for financial crimes compliance.
• Ability to build and scale the function, including hiring, establishing norms, and delivering excellence along the roadmap.
• Establish regular reporting for modelling and analytics.
• Identify areas of opportunity to increase efficiency and precision of the transaction monitoring and sanctions screening program.
• Highlight and escalate deficiencies in the program and develop a solutions-oriented approach for executive leadership.
• Have the technical writing skills to translate code into plain English and vice versa.

Total Rewards Package:

• Base salary
• Equity (stock options)
• Benefits

Salary Range:

• US employees in New York City, Los Angeles, Seattle, or the San Francisco Bay Area: $239,000 - 298,800
• US employees outside of the New York City, Los Angeles, Seattle or the San Francisco Bay Area: $215,100 - 268,900

Diversity & Belonging:

• Mercury values diversity & belonging and is proud to be an Equal Employment Opportunity employer.
• All individuals seeking employment at Mercury are considered without regard to race, color, religion, national origin, age, sex, marital status, ancestry, physical or mental disability, veteran status, gender identity, sexual orientation, or any other legally protected characteristic.
• We are committed to providing reasonable accommodations throughout the recruitment process for applicants with disabilities or special needs.

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About the Role:

As an Applied Research Engineer, you will be the bridge between research, industry, and application shaping the future of our core natural language processing systems. You will be responsible for enabling agentic capabilities across the Hebbia product suite. You will own experiments and POCs focused on combining the latest research findings with specific high-value problems that our customers encounter each and every day.

Responsibilities:

• Focused on LLMs, you will play a crucial role in analyzing and interpreting complex data types to derive and implement cutting-edge insight generation systems.
• Iterate and explore new LLM and NLP techniques maintaining our foothold as an industry leader.
• You will utilize your expertise in statistics, programming, and machine learning to develop and deploy data-driven models and algorithms.
• Your work will contribute to solving business problems, improving processes, and enhancing the overall performance of the company.
• Collaborate with cross-functional teams to improve NLP/LLM capabilities in app.
• Stay up-to-date with the latest advancements and research in the space.
• Collaborate with software engineers to integrate agentic capabilities into existing systems or develop new applications.
• Ensure that systems are efficient, maintainable, and well-monitored.
• Iterate on validation and testing frameworks.

Requirements:

• Bachelor's degree in Computer Science, Engineering, or related field.
• Master's degree in Computer Science, Mathematics, Machine Learning, or a related field is a plus.
• 7+ years software development experience at a venture-backed startup or top technology firm, with a focus on applied machine learning systems.
• Strong programming skills in Python.
• Experience with NLP and text processing libraries such as NLTK, SpaCy, or Apache Tika.
• Experience with Search and Indexing technologies.
• Proficient in machine learning techniques and algorithms.
• Experience working with foundational models and corresponding APIs.
• Knowledge of statistical analysis and data scraping techniques.
• Prior experience in developing NLP models and systems.
• Experience with prompting and building LLM applications and agents is a plus.

Benefits:

• Experience building agentic systems or LLM-enabled products.
• Frequent user of AI products, especially during the development lifecycle (i.e., Cursor, Claude Code, etc).

Compensation:

The salary range for this role is $160,000 to $300,000. This range may be inclusive of several career levels at Hebbia and will be narrowed during the interview process based on the candidate's experience and qualifications. Adjustments outside of this range may be considered for candidates whose qualifications significantly differ from those outlined in the job description.

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What You’ll Be Doing:

• Maintaining and improving existing functionalities within advanced modeling software platforms.
• Understanding and translating technical requirements from customers into robust model solutions.
• Designing innovative, physics-driven model solutions by analyzing measurement data and proposing sophisticated algorithms.
• Creating detailed specifications and comprehensive test plans for proposed model solutions.
• Collaborating with cross-functional teams—including software, hardware, and customer-facing groups—to ensure seamless solution integration.
• Applying modern computational techniques to optimize performance and scalability of modeling components.
• Exploring new modeling approaches and integrating machine learning and image processing methods.

The Impact You Will Have:

• Enhancing Synopsys Proteus OPC modeling solutions to meet the evolving needs of semiconductor customers worldwide.
• Driving innovation in computational lithography and etch modeling, enabling cutting-edge chip design and fabrication.
• Modernizing infrastructure, improving efficiency, and reducing time-to-market for new technology releases.
• Solving challenging problems in advanced software engineering, contributing to Synopsys’ reputation as a technology leader.
• Expanding the capabilities of regression and modeling tools, supporting key industry advancements.
• Enabling successful integration of new modeling techniques, ensuring scalability and reliability for customers.

What You’ll Need:

• MS in CS/EE/Physics/Applied Math or related fields with 8+ years of experience, or PhD with 5+ years.
• Strong programming skills in Python and C++.
• Expertise in data structures and algorithms, with proven experience in parallel computing.
• Deep understanding of physical modeling and statistical analysis/optimization.
• Experience in image/polygon processing; preferred exposure to machine learning, image processing, and computational lithography.

Who You Are:

• Excellent communicator, able to convey complex concepts clearly to technical and non-technical audiences.
• Team player who values collaboration and thrives in a diverse, multidisciplinary environment.
• Curious and eager to learn, always seeking new ways to improve and innovate.
• Detail-oriented with strong analytical and problem-solving skills.
• Adaptable, resilient, and comfortable tackling ambiguous challenges.

The Team You’ll Be A Part Of:

You will join the Synopsys Proteus OPC modeling team, a group dedicated to advanced regression and etch modeling solutions. The team’s core focus is on developing and optimizing model components, exploring new modeling techniques, and modernizing infrastructure to address challenging problems in advanced software engineering. You’ll work alongside experts in computational lithography and software development, collaborating to deliver industry-leading solutions for semiconductor manufacturing.

We Are:

At Synopsys, we drive the innovations that shape the way we live and connect. Our technology is central to the Era of Pervasive Intelligence, from self-driving cars to learning machines. We lead in chip design, verification, and IP integration, empowering the creation of high-performance silicon chips and software content. Join us to transform the future through continuous technological innovation.

Rewards and Benefits:

We offer a comprehensive range of health, wellness, and financial benefits to cater to your needs. Our total rewards include both monetary and non-monetary offerings. Your recruiter will provide more details about the salary range and benefits during the hiring process.

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We are seeking an experienced AI/GenAI engineer to join our team at Synopsys. As a Principal AI/GenAI Engineer, you will design, develop, and deploy GenAI Agentic and machine learning models, algorithms, and systems to tackle complex business challenges.

What You'll Be Doing:

• Design, develop, and deploy GenAI Agentic and machine learning models, algorithms, and systems to tackle complex business challenges.
• Provide technical leadership and mentorship, supporting junior engineers and data scientists in best practices and advanced techniques.
• Stay abreast of the latest AI, Agentic AI, and machine learning advancements, applying them to enhance existing systems or develop innovative solutions.
• Collaborate with program and product managers, software engineers, and stakeholders to define requirements and create technical specifications for AI solutions.
• Conduct data analysis, preprocessing, and feature engineering to prepare datasets for machine learning models.
• Train, validate, and fine-tune machine learning models to meet performance and accuracy benchmarks.
• Deploy AI models into production environments, monitoring and optimizing their performance.
• Document models, algorithms, and methodologies to ensure reproducibility and facilitate knowledge sharing.
• Ensure all AI solutions comply with ethical guidelines, data privacy regulations, and industry standards.

The Impact You Will Have:

• Accelerate innovation in AI-driven products and solutions, directly influencing Synopsys' technological leadership.
• Enhance operational efficiency and decision-making through intelligent automation and data-driven insights.
• Drive adoption of Agentic AI systems, enabling transformative business outcomes across multiple domains.
• Mentor and elevate the technical capabilities of the engineering and data science teams, fostering a culture of excellence.
• Champion ethical AI practices, ensuring responsible development and deployment of cutting-edge technologies.
• Support cross-functional collaboration, bridging the gap between technical and business teams for successful project delivery.
• Contribute to the advancement of semiconductor IPs and EDA tool integration with AI, expanding Synopsys' product portfolio.

What You'll Need:

• Ph.D. or Master’s degree in Computer Science, Data Science, Electrical Engineering, or a related field.
• Minimum 8 years of experience in software engineering, machine learning, and GenAI, with a proven track record in production deployments.
• Strong proficiency in Python; familiarity with backend and distributed systems, message queues, and orchestration technologies is a plus.
• Expertise in data structures, algorithms, and design patterns for scalable AI solutions.
• Extensive experience with machine learning and Agentic frameworks (e.g., TensorFlow, PyTorch, LangChain/LangGraph, AutoGen) and LLM models.
• Strong grasp of statistical analysis, data mining, and data visualization techniques.
• Knowledge of cloud platforms, containerization (Kubernetes, Docker), and version control systems (Git, P4).
• Familiarity with Agile, Kanban, or Scrum methodologies.
• Understanding or experience with semiconductor IPs and EDA tools is highly desirable.

Who You Are:

• Exceptional problem-solving and analytical abilities, with a strategic mindset.
• Strong communication and interpersonal skills to engage diverse audiences.
• Ability to work independently and collaboratively within multidisciplinary teams.
• Demonstrated leadership and mentorship capabilities.
• Adaptable, proactive, and eager to continuously learn and innovate.

The Team You’ll Be A Part Of:

You will join a dynamic, collaborative group of professionals dedicated to advancing AI and GenAI solutions for diverse projects. The team values innovation, knowledge sharing, and continuous improvement, working closely with product managers, engineers, and stakeholders to deliver impactful AI-powered systems. You will play a key role in mentoring, technical leadership, and driving the evolution of Synopsys’ AI initiatives.

Rewards and Benefits:

We offer a comprehensive range of health, wellness, and financial benefits to cater to your needs. Our total rewards include both monetary and non-monetary offerings. Your recruiter will provide more details about the salary range and benefits during the hiring process.

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As a Research Scientist/Engineer focused on honesty within the Finetuning Alignment team, you'll spearhead the development of techniques to minimise hallucinations and enhance truthfulness in language models. Your work will focus on creating robust systems that are accurate and reflect their true levels of confidence across all domains, and that work to avoid being deceptive or misleading.

Responsibilities:

• Design and implement novel data curation pipelines to identify, verify, and filter training data for accuracy given the model’s knowledge
• Develop specialised classifiers to detect potential hallucinations or miscalibrated claims made by the model
• Create and maintain comprehensive honesty benchmarks and evaluation frameworks
• Implement techniques to ground model outputs in verified information, such as search and retrieval-augmented generation (RAG) systems
• Design and deploy human feedback collection specifically for identifying and correcting miscalibrated responses
• Design and implement prompting pipelines to generate data that improves model accuracy and honesty
• Develop and test novel RL environments that reward truthful outputs and penalize fabricated claims
• Create tools to help human evaluators efficiently assess model outputs for accuracy

You may be a good fit if you:

• Have an MS/PhD in Computer Science, ML, or related field
• Possess strong programming skills in Python
• Have industry experience with language model finetuning and classifier training
• Show proficiency in experimental design and statistical analysis for measuring improvements in calibration and accuracy
• Care about AI safety and the accuracy and honesty of both current and future AI systems
• Have experience in data science or the creation and curation of datasets for finetuning LLMs
• An understanding of various metrics of uncertainty, calibration, and truthfulness in model outputs

Strong candidates may also have:

• Published work on hallucination prevention, factual grounding, or knowledge integration in language models
• Experience with fact-grounding techniques
• Background in developing confidence estimation or calibration methods for ML models
• A track record of creating and maintaining factual knowledge bases
• Familiarity with RLHF specifically applied to improving model truthfulness
• Worked with crowd-sourcing platforms and human feedback collection systems
• Experience developing evaluations of model accuracy or hallucinations

Join us in our mission to ensure advanced AI systems behave reliably and ethically while staying aligned with human values.

The annual compensation range for this role is listed below.

For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.

Annual Salary:

$350,000 - $500,000USD

Logistics

Education requirements: We require at least a Bachelor's degree in a related field or equivalent experience.

Location-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.

Visa sponsorship: We do sponsor visas! However, we aren'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.

We 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're interested in this work.

Your 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're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings.

How we're different

We believe that the highest-impact AI research will be big science. At Anthropic we work as a single team to push the boundaries of what is possible with AI.

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Researcher, Synthetic RL

Location

San Francisco

Employment Type

Full time

Department

Research

Compensation

• $295K – $445K • 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 Synthetic RL team develops reinforcement learning methods that leverage synthetic data, environments, and feedback to train and evaluate frontier AI models. The team explores approaches such as self-play, simulators, and other synthetic evaluations to push model capability, generalization, and alignment beyond what is possible with the current prevailing methodology.

About the Role

As a Research Scientist on the Synthetic RL team, you will develop novel reinforcement learning techniques that use synthetic environments and feedback to improve large-scale models. You’ll work closely with other researchers to design experiments, analyze learning dynamics, and translate research insights into training approaches used in production systems.

We’re looking for researchers who enjoy working on open-ended problems, value fast iteration, and want their work to directly shape how frontier models are trained.

This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees.

In this role, you will:

• Research and develop reinforcement learning algorithms

• Design and run experiments to study training dynamics and model behavior at scale

• Collaborate with engineers and researchers to integrate successful approaches into model training pipelines

You might thrive in this role if you:

• Have a strong background in reinforcement learning, machine learning research, or related fields

• Have strong engineering and statistical analysis skills

• Enjoy exploring new problem spaces where data, objectives, and evaluation are imperfect or evolving

• Are motivated by seeing research ideas influence real-world AI systems

About OpenAI

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.

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Research Engineer, Frontier Evals & Environments - Finance

Location

San Francisco

Employment Type

Full time

Location Type

Hybrid

Department

Research

Compensation

• $205K – $380K • 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 Frontier Evals team builds north star model evaluations to drive progress towards safe AGI/ASI. This team builds ambitious evaluations to measure and steer our models, and creates self-improvement loops to steer our training, safety, and launch decisions. Some of the team's open-sourced evaluations include SWE-bench Verified, MLE-bench, PaperBench, and SWE-Lancer, and the team built and ran frontier evaluations for GPT4o, o1, o3, GPT 4.5, ChatGPT Agent, and GPT5. If you are interested in feeling firsthand the fast progress of our models, and steering them towards good, this is the team for you.

About you

We seek exceptional research engineers that can push the boundaries of our frontier models in the finance domain. We are looking for those who will help shape AI evaluations of financial reasoning and related capabilities, and will own individual threads within this endeavor end-to-end.

In this role, you'll:

• Identify important model capabilities, skills, and behaviors that are crucial to financial workflows, and design methods to quantify performance in these areas

• Own and pursue a research agenda to identify an important model capability (especially as it relates to financial reasoning) and build evals to measure it

• Continuously refine evaluations of frontier AI models to assess the extent of frontier capabilities

We expect you to:

• Have strong engineering and statistical analysis skills (with at least 2-3 years of full-time technical experience)

• Be passionate about evals for real world applications and knowledge work

• Be detail-oriented and thorough

• Be a team player / willing to do a variety of tasks to move the team forward

• Be passionate and knowledgeable about AGI/ASI measurement

• Be able to operate effectively in a dynamic and extremely fast-paced research environment as well as scope and deliver projects end-to-end

It would be great if you also have:

• An ability to work cross-functionally

• Excellent communication skills

About OpenAI

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.

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Location

San Francisco

Employment Type

Full time

Location Type

Hybrid

Department

Data Science

Compensation

• $266K – $385K • 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 UX Research team is a small team with outsized impact across OpenAI. We sit at the intersection of users, product, and safety—helping ensure that powerful AI systems are built responsibly and grounded in real human needs.

Our work informs critical product decisions across OpenAI. We partner closely with product, design, engineering, and leadership to bring clarity to complex questions—often in fast-moving spaces where norms and best practices are still being defined.

This role is based in San Francisco, CA. We operate on a hybrid model with 3 days in the office each week and offer relocation assistance.

In this role, you will:

• Design and execute quantitative research across the product lifecycle, from foundational understanding to concept validation, prototyping, and usability evaluation.

• Partner with product managers, designers, engineers, and data scientists to identify high-impact opportunities where quantitative insights can meaningfully shape product decisions.

• Lead rigorous, customized studies that answer both strategic and tactical questions, using methods such as surveys, experiments, and behavioral data analysis.

• Translate complex data into clear, actionable recommendations that drive alignment and decision-making across teams.

• Apply strong survey methodology and statistical rigor to ensure findings are valid, reliable, and decision-ready.

• Influence product direction through close cross-functional collaboration and clear, audience-appropriate storytelling.

You might thrive in this role if you have:

• 5+ years of experience working in user experience research, market research, data science, and/or a related field with a strong focus on quantitative methods.

• Expertise in quantitative research, with proficiency in statistical analysis, experimental design, survey methodology, and behavioral data analysis.

• Strong data analysis skills using tools such as SQL and Python.

• Exceptional written and verbal communication skills, with the ability to influence decision-making at all levels.

• Proven experience leading quantitative research projects that have made a lasting impact on product and design decisions.

• Experience working with senior stakeholders.

• A drive for excellence and the ability to consistently raise the bar.

About OpenAI

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.

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San Mateo, CA, United States

Early Career

ID: 5825

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.

We’re on a mission to connect a billion people with optimism and civility, and looking for amazing talent to help us get there.

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.

WHY DATA SCIENCE & ANALYTICS?

The Data Science & Analytics organization's mission is to increase our speed, frequency, and acumen in 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, experimentation, causal inference, statistical modeling, and machine learning. Aligned and partnered with product verticals, we use this extensive tool belt to discover new opportunities and unmet use cases, influence and craft the product roadmap, and prioritize, build data products, and measure impact on our community of players and developers.

WHY GENERATIVE AI?

Our team’s mission is to enable Roblox Creators to bring GenAI capabilities to millions of users. We drive this innovation with a core commitment to safety, responsibility, and quality.

As a Data Scientist, you will play a critical role in evaluation and optimization for user-facing GenAI systems (such as text, image, video, 3D, 4D). You will define how we measure safety, responsibility, quality, and efficiency. You will combine annotation analysis, design of experiments, causal inference, model-based evaluation methods (such as LLM-as-a-judge), optimization algorithm, and AI models to drive product decisions and model improvements.

You Will:

• Develop Evaluation Frameworks: Design and operationalize rigorous evaluation systems for either GenAI features (text, image, video, 3D, 4D). This includes eval experiment design, dataset design, label reliability analysis, and implementing and finetuning LLM-as-judge methods.

• Run Rigorous Experiments: Conduct online experiments (A/B tests) and causal inference to quantify the impact of GenAI features. You will identify opportunities, measure lift, and ensure statistical rigor.

• Define Success Metrics: Partner with cross-functional teams to define leading/lagging indicators for GenAI feature user satisfaction, business success, and safety.

• Build Automated Systems: Research and apply state-of-the-art methodologies to build reproducible evaluation tooling that lift rigor and efficiency across the company.

• Conduct Applied Research at the Frontier: Maintain an active pulse on the intersection of Gen AI and Data Science. You will innovate on methodology and techniques to solve unique business challenges while contributing to the broader field in the technical community.

You Have:

• Possess or pursuing a PhD or equivalent in Statistics, Economics, Computer Science, Applied Math, Physics, Engineering, or a related quantitative field.

• Technical Proficiency: Strong proficiency in SQL (Hive/Spark) for manipulating large datasets and scripting languages (Python or R) for analysis and modeling.

• Experimentation and Causal Inference: A solid grounding in experimentation, causal inference, and statistical analysis, including test design and metric design for feature impact.

• Problem Solving: A demonstrated track record of framing ambiguous problems, designing analytical approaches, and solving open-ended data science problems that drive business impact.

• Learning Agility: Ability to effectively and responsibly use AI tools to enhance productivity and a passion for continuously improving methods in a fast-evolving field.

• GenAI Familiarity: Familiarity with GenAI models and safety/quality evaluation methods. Expertise in the model training lifecycle is a plus (e.g., fine-tuning, RLHF, or synthetic data generation).

• Applied Research Background: A track record of applied research or publications in relevant technical fields is highly valued.

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 salary could fall outside of this expected range. This pay range is subject to change and may be modified in the future. All full-time employees are also eligible for equity compensation and for benefits as described on this page.

Annual Salary Range

$185,860—$221,380 USD

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

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What you'll do

• Planning and execution of engine or vehicle development program
• Calibration dataset development in-line with guidelines for the relevant attributes

What you need

• BEng in Mechanical/Automotive or related engineering discipline

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What you'll do

Discover and validate online signals from user interactions that serve as reliable proxies for true answer quality.

• Design and implement novel online metrics to be tracked both in A/B testing and on product health dashboards, ensuring alignment with ground-truth evaluations.

What you need

• Strong proficiency in Python and SQL (expected to write production-grade code).

Why this matters

Your work directly shapes how Perplexity measures and improves Answer Quality, driving product decisions and user satisfaction.

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What you'll do

• Define and maintain product KPIs for subscription and platform performance.
• Build dashboards and reporting to monitor acquisition, engagement, and retention.

What you need

• Bachelor’s degree in analytics, economics, statistics, or related field.

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What you'll do

• Champion analytics projects from the conceptual stages through communication of results and recommendations
• Use player data to perform behavioural analysis, clustering analysis, predictive modeling, hypothesis testing, and more

What you need

• 5+ years of experience applying quantitative or statistical methods to produce insights from data

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What you'll do

• Collaborate with product managers and data analysts to identify business opportunities and develop data-driven solutions
• Develop and maintain data pipelines to support business needs
• Create data visualizations to inform business decisions

What you need

• 7+ years of experience in data science or a related field
• Strong programming skills in languages such as Python or R
• Experience with data visualization tools such as Tableau or Power BI
• Strong analytical and problem-solving skills

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What you'll do

You will join us as a Player Experience (PX) Researcher, focused on enhancing player experience across Sims products. You will guide game development by collaborating with teams to shape strategy and the player experience.

• Collaborate with game teams to align research with franchise goals and strategies.
• Partner with diverse teams to create insights that influence franchise direction.
• Present player insights and recommended actions to game teams and leadership, empowering data-informed decisions.
• Refine and enhance departmental research processes to increase efficiency and influence.

What you need

• Degree in a related field (e.g., Psychology, Market Research, Data Science, HCI), or equivalent industry experience.
• Experience leading research projects from planning to delivery.
• 3+ years of industry experience conducting user research across platforms.
• Team-oriented, collaborative, and comfortable working across time zones and remotely.
• Familiarity with statistical analysis tools and methods.

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