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We are looking for a Principal Data Scientist leader, creative modeling geeks who are willing to work in a dynamic environment to solve real life day to day problems, leveraging data science techniques. You will enjoy and be successful in this role if you are curious and willing to challenge the status quo and come up with data driven solutions to ambiguous problems.

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+ year(s) 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 of experience in at least one of programming languages like Python/R/MATLAB/C#/Java/C++
• Experience in applying statistics, designing experimentation and metrics particularly in Advertising platforms.

Preferred Qualifications:

• Organizational, analytical, data science skills and intuition .
  
• Problem solver: ability to solve problems that the world has not solved before ,
  
• Interpersonal skills: cross-group and cross-culture collaboration.
  
• Experience with real world system building and data collection, including design, coding and evaluation.
  
• Excellent communication to be able to communicate insights to senior leaders.
  
• Experience with driving large collaboration across multiple teams.
  
• Experience with communicating with different audiences to provide insights.
  
• Demonstrated experience in applying statistics, experimentation and metrics to generate clear actionable insights.

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, 30 2025.

#MicrosoftAI

• Measurement: Define, invent, and deliver metrics which accurately measure user and business value across various products and marketplace components.
• Experimental Design: Think critically about sampling and experimental design across User and Demand dimensions.
• Product Iteration: Interpret the results of analyses, validate approaches, and learn to monitor, analyze, and iterate to continuously improve.
• Cooperation: Partner effectively with program management, engineers, and other areas of the business across our Consumer online business
• Influence: engage with stakeholders to produce clear, compelling, and actionable insights and data-science driven workflows that influence product and service improvements.
• Make independent decisions for the team and handle difficult tradeoffs.
• Translate strategy into plans that are clear and measurable, with progress shared out monthly to stakeholders.