Help shape how Windows is built and shipped by leading the technical vision and quality systems for Windows-wide experimentation to deliver fast, safe, trustworthy decisions at scale.
Requirements
- Doctorate in Statistics, Biostatistics, Econometrics, Economics, Quantitative Social Sciences, Data Science, Operations Research, Mathematics, Computer Science, or related field AND 5+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
- Master's Degree in Statistics, Biostatistics, Econometrics, Economics, Quantitative Social Sciences, Data Science, Operations Research, Mathematics, Computer Science, or related field AND 7+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
- Bachelor's Degree in Statistics, Biostatistics, Econometrics, Economics, Quantitative Social Sciences, Data Science, Operations Research, Mathematics, Computer Science, or related field AND 10+ years data science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
- equivalent experience
- 2+ years of additional experience applying data science techniques in a business or applied research setting
- 2 years of the required work experience includes working on or in close partnership with an experimentation platform or other highly scaled Data Science capability.
- 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.
Responsibilities
- Define and implement clear, practical guidance on experimental design, measurement, and decision frameworks so teams can make faster, higher-quality decisions.
- 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.
- Partner with Windows Experimentation colleagues to improve insight generation while reducing manual work through automation and reusable assets.
- Create clarity across Windows PM, Engineering, and Data Science teams; land common practices; reduce duplicated effort; improve decision quality.
- Provide hands-on technical and career mentorship for earlier-career data scientists; lead reviews and learning sessions; and contribute to hiring practices.
- 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.
Other
- Lead the technical vision and quality systems for Windows‑wide experimentation
- 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.
- 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.
- Experience collaborating with engineering and product teams to build and scale experimentation platforms and large‑scale measurement systems.
