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Help shape how Windows is built and shipped. Lead the technical vision and quality systems for Windows‑wide experimentation to deliver fast, safe, trustworthy decisions at scale. 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 Principal Data Scientist on the Windows Experimentation team, you will define and execute the technical vision and best practices for Windows‑wide experimentation—spanning safe software deployment and product development. You’ll own the design and adoption of measurement and decision frameworks that make experimentation fast, reliable, and trustworthy at scale. This role emphasizes technical leadership, ownership, and influence across organizational boundaries. You’ll build durable partnerships and practices with product PM, Engineering, and DS teams across Windows—actively shaping and raising the bar on experimentation culture and decision quality. 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.
Job Responsibility:
Set and land experimentation best practices across Windows
Own experimentation quality systems
Build next‑generation measurement capabilities
Lead through influence to drive alignment and adoption
Multiply impact by developing talent and raising the bar for the craft
Represent Windows Experimentation externally and drive innovation
Embody our culture and values
Requirements:
Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 5+ years data-science experience
OR Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 7+ years data-science experience
OR Bachelor's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 10+ years data science experience
OR equivalent experience
2+ years of additional experience applying data science techniques in a business or applied research setting
2+ years experience working on, or in close partnership with, an experimentation platform or other highly scaled Data Science capability
Demonstrated track record of landing experimentation standards and influencing adoption across multiple teams or organizations, improving decision quality and time‑to‑decision at product scale
Deep expertise in advanced experimentation methods, such as complex experimental designs, adaptive experiments (e.g., bandits), anytime‑valid approaches, causal inference, and experimentation in multi‑sided marketplaces
Experience collaborating with engineering and product teams to build and scale experimentation platforms and large‑scale measurement systems
History of mentoring data scientists and upskilling teams through coaching, leading learning forums, and contributing to hiring practices
Active engagement with the broader experimentation and causal inference community (e.g., publishing, conference talks, or open‑source contributions)