Data Scientist II

Microsoft•Redmond, WA

70d

About The Position

As a Data Scientist II on the Windows Data Team, you will play a pivotal role in driving AI-powered innovation across the software development lifecycle. You will collaborate with cross-functional teams—including product management, engineering, design, and user research—to embed data-driven thinking into every stage of product development. Your responsibilities include designing and executing growth experiments, analyzing business metrics, building scalable data pipelines, and delivering actionable insights that influence product direction. You will identify instrumentation needs, define and set up metrics and OKRs, and evaluate the return on investment for new ideas. You will also build predictive models to understand customer behavior, drive personalized features, and support targeted outreach efforts. You will be expected to develop operational models at scale, conduct reviews of data analysis and modeling techniques, and invent new evaluation methods. Your work will contribute to thought leadership and best practices across the organization. Effective communication and collaboration skills are essential, as you will work in complex, ambiguous environments and apply strategic influence to deliver measurable results. Microsoft’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.

Requirements

Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field OR Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 1+ year(s) data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) or consulting experience OR Bachelor's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 2+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) OR equivalent experience.
Ability to meet Microsoft, customer and/or government security screening requirements are required for this role.
Microsoft Cloud Background Check: This position will be required to pass the Microsoft Cloud background check upon hire/transfer and every two years thereafter.

Nice To Haves

Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 1+ year(s) data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 3+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
Bachelor's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 5+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
OR equivalent experience.
Extensive experience in exploratory data analysis, statistical inference, predictive modeling (e.g., regression, classification), and time-series forecasting to uncover trends and drive decision-making.
Designed and analyzed experiments to validate hypotheses, optimize product features, and measure impact across diverse business scenarios.
Built and maintained scalable data pipelines to support machine learning workflows, enabling efficient data ingestion, transformation, and model deployment.
Demonstrated leadership in complex problem spaces through strategic thinking, technical depth in ML and data engineering, and a relentless drive for innovation and progress.

Responsibilities

Partner cross-functionally with product, engineering, design, and research teams to embed data-driven thinking throughout the product lifecycle.
Experience in building data pipelines.
Deliver actionable insights and predictive models that shape product direction and customer engagement.
Define instrumentation requirements, establish metrics and OKRs, and drive personalized features.
Review and innovation on data analysis, modeling techniques, and evaluation methods.
Champion thought leadership, strategic influence, and effective communication in complex, ambiguous environments.
Design and execute growth experiments, analyze business metrics, and evaluate ROI to guide strategic decisions.

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