• Senior Data Scientist

    Microsoft Corporation (Redmond, WA)


    Do you want to shape how Windows is built and shipped? Join the team behind the experimentation engine that powers product innovation and deployment decisions. At **Windows Experimentation** , we help teams move fast and ship smart by delivering trusted insights through randomized controlled trials.

     

    As a **Senior Data Scientist** on the **Windows Experimentation** team, you’ll build the statistical and technical foundations that power experimentation across the Windows ecosystem. Your work will enable product teams to test new features with confidence and help engineering and release teams make data-driven decisions about shipping Windows. You’ll collaborate across disciplines to design scalable systems, improve causal inference methods, and ensure that experimentation is fast, reliable, and trustworthy.

     

    This role offers high-impact work at the intersection of science, engineering, and product; a deep focus on experimentation infrastructure, causal inference, and telemetry at scale; and the opportunity to shape how Microsoft builds and ships Windows to more than a billion devices.

     

    Microsoft’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.

    Responsibilities

    + Develop and apply statistical methods to support randomized controlled trials (RCTs) that inform both product development and deployment decisions across the Windows ecosystem.

    + Design scalable systems and tooling that enable rigorous, high-throughput experimentation across the Windows ecosystem.

    + Partner with engineering, product, and data science teams to define metrics, validate experimental designs, and ensure robust causal inference.

    + Investigate experiment outcomes and anomalies to surface insights, improve decision quality, and strengthen system observability.

    + Advance experimentation best practices by contributing to internal guidance, tooling, and methodology.

    + Stay current with advances in causal inference, experimentation platforms, and statistical methodology and bring fresh thinking from academia and industry into our work.

    Qualifications

    Required Qualifications:

    + Doctorate in Statistics, Biostatistics, Econometrics, Economics, Quantitative Social Sciences, Data Science, Operations Research, Mathematics, Computer Science, or a related field **AND** 1+ year(s) data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)

    + **OR** Master's Degree in Statistics, Biostatistics, Econometrics, Economics, Quantitative Social Sciences, Data Science, Operations Research, Mathematics, Computer Science, or a related field **AND** 3+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)

    + **OR** Bachelor's Degree in Statistics, Biostatistics, Econometrics, Economics, Quantitative Social Sciences, Data Science, Operations Research, Mathematics, Computer Science, or a related field **AND** 5+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)

    + **OR** equivalent experience

    + 2+ years of experience applying data science techniques in a business or applied research setting

    Preferred Qualifications:

    + Experience applying causal inference techniques to drive product development or applied research outcomes.

    + Experience designing and implementing complex experimental designs (e.g., factorial, adaptive, or sequential designs; bandits) in any domain.

    + Experience collaborating with engineering and product teams to build scalable data science capabilities (e.g., experimentation platforms, ML infrastructure, or similar).

     

    Data Science IC4 - The typical base pay range for this role across the U.S. is USD $119,800 - $234,700 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $158,400 - $258,000 per year.

     

    Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here: https://careers.microsoft.com/us/en/us-corporate-pay

     

    Microsoft will accept applications for the role until **October 14, 2025.**

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    Microsoft is an equal opportunity employer. Consistent with applicable law, all qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations (https://careers.microsoft.com/v2/global/en/accessibility.html) .