Data Scientist - Pricing

• Data Analysis & Modeling: Analyze large-scale datasets to identify patterns, trends, and opportunities for improving yield and efficiency.
• Yield Optimization: Develop machine learning models to optimize resource allocation and pricing strategies.
• Cross-Functional Collaboration: Partner with business planning, engineering, product management, and finance teams to align yield strategies with business objectives.
• Experimentation & A/B Testing: Design and execute experiments to validate optimization hypotheses. Build causal inference models (e.g., difference-in-difference, synthetic control) to measure the impact of business decisions.
• Data Visualization: Develop dashboards and other visuals to monitor key business trends, identify new opportunities, and translate findings to actionable insights.
• Thought Leadership: Stay current with industry trends in AI, cloud economics, and optimization techniques; share insights and best practices internally.
• Other: Embody our Culture and Values

• 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.

Additional or 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.

Experience in Python, R, or similar languages

Experience with Azure Machine Learning (ML) or equivalent cloud-based ML platforms.

Experience working with large-scale data and distributed systems.

Experience with yield or revenue management, pricing optimization, or cloud resource allocation.

Data Science IC3 - The typical base pay range for this role across the U.S. is USD $102,100.00 - $202,200.00 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 $133,800.00 - $219,200.00 per year.

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.