OverviewMicrosoft Copilot is building an ecosystem of AI-powered consumer experiences across Search, Copilot, Edge, MSN, and beyond. The MAI Ecosystem Data Science team defines the metrics, experimentation frameworks, and measurement systems that shape how Microsoft AI evaluates success, identifies opportunities, and makes investment decisions at scale.
We are seeking a Principal Data Scientist to lead ecosystem-level measurement strategy across products and businesses. In this role, you will develop the scientific foundations that guide some of Microsoft's most important AI investments, partnering closely with product, engineering, business, and executive leaders to influence strategy, execution, and resource allocation.
The ideal candidate combines deep expertise in experimentation, statistics, metrics, and causal inference with exceptional business judgment and influence. You thrive in ambiguity, challenge assumptions with data, and transform complex signals into clear decisions that drive product and business impact.
This is a unique opportunity to shape how Microsoft AI measures value across the ecosystem, uncover new growth opportunities, and help define the future of AI-powered consumer experiences.
Starting January 26, 2026, Microsoft AI (MAI) employees who live within a 50- mile commute of a designated Microsoft office in the U.S. or 25-mile commute of a non-U.S., country-specific location are expected to work from the office at least four days per week. This expectation is subject to local law and may vary by jurisdiction.
Responsibilities- Define the measurement strategy, metrics, and decision frameworks that guide product and investment decisions across the Microsoft AI ecosystem.
- Lead ecosystem-level analyses, experimentation, and causal inference to uncover opportunities, quantify impact, and drive business outcomes.
- Partner across product, engineering, business, and executive leadership teams to shape strategy, roadmap priorities, and resource allocation.
- Identify emerging opportunities, risks, and market dynamics before they become visible in product-level metrics.
- Design and evolve North Star metrics and evaluation systems that accurately measure user value, business impact, and long-term ecosystem health.
- Drive alignment and execution across organizations through influence, scientific rigor, and trusted partnerships.
- Raise the bar for analytical excellence through technical leadership, mentorship, and best practices in measurement, experimentation, and data science.
QualificationsRequired Qualifications:- Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 3+ 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 5+ 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 7+ 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 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 8+ 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.
- 6+ years of experience in Python, R, C++, Java, C#, or similar programming languages.
- Demonstrated expertise in statistics, experimentation, causal inference, and large-scale data analysis.
- Experience developing metrics, evaluation frameworks, and measurement systems that drive product and business decisions.
- Proven track record of identifying high-impact opportunities and solving complex, ambiguous problems across multiple organizations.
- Experience influencing product strategy and driving alignment among stakeholders with differing objectives through data-driven insights and recommendations.
- Exceptional written and verbal communication skills, with the ability to translate complex technical concepts into clear guidance for executive and non-technical audiences.
- Experience leading large cross-functional initiatives and collaborating effectively across product, engineering, business, and analytics teams without direct authority.
- Experience building and evaluating production-scale data, analytics, machine learning, or experimentation systems.
#MicrosoftAI
Data Science IC5 - The typical base pay range for this role across the U.S. is USD $142,800 - $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
This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled.
