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Home›Jobs›Microsoft›Data Scientist II
Microsoft

About Microsoft

Empowering every person and organization on the planet

🏢 Tech👥 100K+📅 Founded 1975📍 Redmond, Washington, United States

Key Highlights

  • Market cap exceeds $2 trillion
  • 100,000+ employees worldwide
  • Leading cloud services through Azure
  • Major clients include Walmart and BMW

Microsoft Corporation, headquartered in Redmond, Washington, is a leading technology company known for its software products like Windows and Office, as well as cloud services through Azure. With over 100,000 employees, Microsoft serves millions of customers globally, including major enterprises lik...

🎁 Benefits

Microsoft offers competitive salaries, stock options, generous PTO policies, and comprehensive health benefits. Employees also enjoy a flexible remote...

🌟 Culture

Microsoft fosters a culture of innovation and inclusivity, emphasizing collaboration across teams and a commitment to diversity. The company values em...

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Microsoft

Data Scientist II

Microsoft • United States, Washington, Redmond

Posted 3w ago🏛️ On-SiteMid-LevelData scientist📍 Redmond
Apply Now →

Skills & Technologies

PythonSQLMachine learningData analysisPredictive modelingData visualization

✨ AI Summary

Microsoft is hiring a Data Scientist II to drive AI-powered innovation within the Windows Data Team. You'll collaborate with cross-functional teams to design growth experiments and build scalable data pipelines. This role requires expertise in Python, SQL, and machine learning techniques.

Job Description

Overview
As a Data Scientist II on the Windows Data Team, you will play a pivotal role in driving AI-powered innovation across the software development lifecycle. You will collaborate with cross-functional teams—including product management, engineering, design, and user research—to embed data-driven thinking into every stage of product development.

Your responsibilities include designing and executing growth experiments, analyzing business metrics, building scalable data pipelines, and delivering actionable insights that influence product direction. You will identify instrumentation needs, define and set up metrics and OKRs, and evaluate the return on investment for new ideas. You will also build predictive models to understand customer behavior, drive personalized features, and support targeted outreach efforts.
You will be expected to develop operational models at scale, conduct reviews of data analysis and modeling techniques, and invent new evaluation methods. Your work will contribute to thought leadership and best practices across the organization. Effective communication and collaboration skills are essential, as you will work in complex, ambiguous environments and apply strategic influence to deliver measurable results.

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
• Partner cross-functionally with product, engineering, design, and research teams to embed data-driven thinking throughout the product lifecycle.
• Experience in building data pipelines.
• Deliver actionable insights and predictive models that shape product direction and customer engagement.
• Define instrumentation requirements, establish metrics and OKRs, and drive personalized features.
• Review and innovation on data analysis, modeling techniques, and evaluation methods.
• Champion thought leadership, strategic influence, and effective communication in complex, ambiguous environments.
• Design and execute growth experiments, analyze business metrics, and evaluate ROI to guide strategic decisions.


Qualifications

Required Qualifications: 

  • Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field
    • OR Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 1+ year(s) data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) or consulting experience
    • OR Bachelor's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 2+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
    • OR equivalent experience. 

Other Requirements: Ability to meet Microsoft, customer and/or government security screening requirements are required for this role. These requirements include but are not limited to the following specialized security screenings:

  • Microsoft Cloud Background Check: This position will be required to pass the Microsoft Cloud background check upon hire/transfer and every two years thereafter. 

Preferred Qualifications: 

  • Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 1+ 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 3+ 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 5+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) 
    • OR equivalent experience. 
  • Extensive experience in exploratory data analysis, statistical inference, predictive modeling (e.g., regression, classification), and time-series forecasting to uncover trends and drive decision-making.
  • Designed and analyzed experiments to validate hypotheses, optimize product features, and measure impact across diverse business scenarios.
  • Built and maintained scalable data pipelines to support machine learning workflows, enabling efficient data ingestion, transformation, and model deployment.
  • Demonstrated leadership in complex problem spaces through strategic thinking, technical depth in ML and data engineering, and a relentless drive for innovation and progress.

#W+DJOBS

 

 

 

 

 

 



 



Data Science IC3 - The typical base pay range for this role across the U.S. is USD $100,600 - $199,000 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 $131,400 - $215,400 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.




Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance with religious accommodations and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.

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