Principal Data Science Manager

Microsoft AI (MAI) creates innovative AI-powered and personalized web experiences in Microsoft Windows, Edge & Bing, that inform, entertain, add value, save money, and breathe productivity into the life and work of millions of customers. MAI makes the web work for our consumers, advertisers, and publishers in a safe environment where everyone can get informed, entertained, save money and thrive!

MSN is a personalized content feed powering user experiences across Microsoft. Our mission is to empower every person on the planet to be informed, entertained, and inspired. We are looking for an experienced Principal Data Science Manager to join our Growth and Analytics team.

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.

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.

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.
• 5+ years experience in data science modeling, statistics, analytics, business intelligence, or data-driven business strategy.  
• 3+ years people-management experience.
   

Preferred Qualifications:

• Previous product analytics, web analytics and or content analytics experience. 
• Interpersonal communication and ability to leverage the data to tell a story. 
• Demonstrated stakeholder management ability including effective prioritization, clear and concise communication, and delivery of actionable data-driven insights. 
• Knowledge on big data processing from raw events to metrics and insights (PySpark/Scala).
• Knowledge of Content ecosystem, Ads and online shopping metrics.

Data Science M5 - 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 November 25, 2025.

#MicrosoftAI

• Work with a host of engaged stakeholders who value your skills and consider you thought partners in driving the business. 
• Lead a team of data scientists and empower them to do their best work.
• Collaborate with cross-functional teams to understand features, estimate impacts and drive the engagement improvements based on insights from big data.
• Enhance products by evaluating performance metrics and user feedback. Develop self-service dashboards and reports for various stakeholders using reporting platforms.
• Analyze large datasets to identify patterns, trends, and content performance to improve the relevance and quality of our recommendation systems. 
• Build metrics system to measure Business Health and quickly identify the root cause when metrics moves.
• Conduct business modeling to identify growth opportunities and initiate projects with a positive long-term ROI.
• Design and conduct A/B tests to evaluate algorithm performance and proposing iterative improvements based on the results. 
• Effectively communicate findings, insights, and recommendations to both technical and non-technical stakeholders, enabling informed decision-making.