Data Scientist II

• Build and deploy machine learning models and statistical analyses to improve platform performance, reliability, and cost efficiency.

• Partner with engineering teams to integrate predictive insights into distributed systems and services.

• Design and analyze experiments (e.g., A/B tests) to validate hypotheses and measure impact on customer experience and platform health.

• Develop dashboards and metrics to monitor model performance and service health.

• Communicate findings and recommendations to technical and business stakeholders through clear, actionable insights.

• Collaborate with cross-functional teams to ensure data quality and effective use of analytics in decision-making.

• 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.

• 2+ years of experience in data science, analytics, or related areas.

• 2+ years of experience in applied machine learning, statistical modeling, and experimentation.

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.

• Proficiency in Python for data analysis and model development.

• Experience with SQL and working with large datasets.

Microsoft is a global technology company headquartered in Redmond, Washington. Our mission is to empower every person and every organization on the planet to achieve more. We develop, license, and support a wide range of software products, services, and devices that help individuals and businesses realize their full potential.

Our flagship products include the Microsoft 365 productivity cloud, Windows operating system, Azure cloud platform, and Dynamics 365 business applications. We are also a leader in areas such as artificial intelligence, cybersecurity, developer tools, and gaming through Xbox and Game Pass.

With operations in more than 190 countries and over 220,000 employees worldwide, Microsoft is committed to responsible innovation, inclusive economic growth, and sustainability. We work closely with governments, industries, and communities to ensure that technology serves the public good and helps address some of the world’s most pressing challenges.

As we celebrate our 50th anniversary in 2025, we continue to look forward—investing in AI, cloud, and quantum computing to shape the future of work, education, and society at large scale.