Principal Data Scientist

Microsoft • Redmond, WA

1d • $139,900 - $274,800

About The Position

Overview
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.

Requirements

• Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 5+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
• OR Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 7+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
• OR Bachelor's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 10+ years data science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
• OR equivalent experience.

Nice To Haves

• 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).

Responsibilities

• Set and land experimentation best practices across Windows. Define and implement clear, practical guidance on experimental design, measurement, and decision frameworks so teams can make faster, higher‑quality decisions.
• Own experimentation quality systems. Maintain and evolve guardrails, scorecards, and decision mechanisms to deliver trustworthy insights at Windows scale. Lead root‑cause investigations and post‑mortems when results conflict or regressions appear, and drive fixes into practice.
• Build next‑generation measurement capabilities. Partner with Windows Experimentation colleagues to improve insight generation while reducing manual work through automation and reusable assets.
• Lead through influence to drive alignment and adoption. Create clarity across Windows PM, Engineering, and Data Science teams; land common practices; reduce duplicated effort; improve decision quality.
• Multiply impact by developing talent and raising the bar for the craft. Provide hands‑on technical and career mentorship for earlier‑career data scientists; lead reviews and learning sessions; and contribute to hiring practices.
• Represent Windows Experimentation externally and drive innovation. Share work at academic and industry forums, stay current on advances in experimentation and causal inference, pilot new approaches, and embed successful techniques into practice and the platform.
• Embody our culture and values.

What This Job Offers

• Job Type: Full-time
• Career Level: Principal
• Education Level: Ph.D. or professional degree