Principal Data Scientist

The Outlook Data and AI Platform team is seeking a Principal Data Science Leader to shape our data strategy, drive innovation, and build the data culture that powers Copilot and AI transformation at scale. This leader will be responsible for advancing our data science capabilities, defining product analytics best practices, and creating the data flywheel that accelerates impact across engineering, product, and customer experiences. 

As a Principal Data Scientist, you will partner with executives, product teams, and engineers to define the future of Outlook data and AI. You will be expected to provide strategic guidance, lead large-scale initiatives, and mentor peers while translating data insights into measurable business and product outcomes.

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

• Define and execute a long-term vision for data science, analytics, and evaluation frameworks.
• Shape the data flywheel by creating scalable measurement and feedback loops that continuously improve product performance and user experience.
• Influence product and business strategy by synthesizing data, insights, and emerging research into actionable recommendations for senior leadership.
• Lead large-scale, cross-functional programs for data-driven evaluation, experiment pipelines, and automated measurement systems.
• Build, scale, and promote a culture of data-informed decision making across engineering, product, and business teams.
• Manage, coach and mentor data scientists and analysts, fostering excellence in experimentation, analytics, and business impact.
• Design and implement advanced statistical and machine learning methods to measure product effectiveness and uncover actionable insights.
• Establish and champion product analytics best practices (e.g., metric design, funnel analysis, experiment setup, and decision frameworks).
• Lead the design, execution, and analysis of A/B tests and other controlled experiments.
• Drive acquisition, management, and analysis of large-scale datasets to inform engineering and product innovation.
• Partner with engineers, designer, user researchers, and product managers to align data initiatives with product roadmaps and customer needs.
• Ensure seamless integration of evaluation and analytics into product workflows, from design through deployment.
• Serve as a trusted thought leader to executive stakeholders, communicating complex findings in a clear, actionable way.

Qualifications

Required Qualifications:

• 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.
• Advanced knowledge of probability, statistics, experimental design, and product analytics, with a strong track record in designing and leading A/B tests, funnel analysis, and metric frameworks.
• Proficiency in large-scale data management and analysis using tools such as SQL, Python, R, Spark, or similar technologies.
• Good communication skills with the ability to collaborate effectively across teams and influence senior leadership. Strong business insight to translate data-driven findings into strategic and product outcomes.
• 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.

Preferred Qualifications:

• Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 8+ 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 10+ 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 12+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) OR equivalent experience.
• OR Master'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 Bachelor's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 12+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) OR equivalent experience.

Data Science IC5 - The typical base pay range for this role across the U.S. is USD $139,900 - $274,800 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 $188,000 - $304,200 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 22nd, 2025.

Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, color, family or medical care leave, gender identity or expression, genetic information, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran status, race, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable laws, regulations and ordinances.  We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you need assistance and/or a reasonable accommodation due to a disability during the application or the recruiting process, please send a request via the Accommodation request form.

Benefits/perks listed below may vary depending on the nature of your employment with Microsoft and the country where you work.