We are seeking a Senior Data Scientist to help shape the Microsoft consumer eCommerce experience by applying data science and emerging AI to some of our most important customer and business opportunities. You will combine advanced analytics, experimentation, machine learning, and innovative technologies to develop solutions that improve how our teams understand customers, generate insights, and make decisions.
This role sits at the intersection of data science, applied AI, and user-centered innovation. You will partner across business and technical teams to understand key users, scenarios, and decisions, rapidly test new approaches, and translate ideas into scalable capabilities. Success in this role goes beyond building technical models. It means creating analytical solutions that are intuitive, relevant, actionable, and ultimately adopted by the people they are designed to support.
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
Apply data science techniques to customer and business problems, including machine learning, statistical analysis, experimentation, causal inference, segmentation, forecasting, and predictive modeling.
Translate ambiguous business and user needs into clear analytical approaches and scalable solutions.
Develop solutions around specific users and decision-making scenarios, making insights easier to discover, understand, and act upon.
Explore and apply emerging technologies, including generative AI, large language models, and AI agents, to improve insight generation and analytical experiences.
Rapidly prototype and evaluate new approaches, balancing technical proficiency with speed and practical business value.
Build and operationalize analytical and machine learning solutions in partnership with engineering and other technical teams.
Determine when traditional analytics, machine learning, generative AI, or a combination of approaches is most suited to solve a problem.
Evaluate solutions based on both technical quality and real-world effectiveness, including usability, adoption, decision quality, and business impact.
Communicate analytical concepts, findings, and recommendations clearly to both technical and non-technical audiences.
Develop reusable analytical methods, frameworks, and capabilities that can scale across users and business scenarios.
Embody our culture and values.
Qualifications
Required 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.
Preferred Qualifications
Experience applying data science, machine learning, applied statistics, or related quantitative techniques to real-world business problems.
Experience working with large, complex datasets using Python and SQL
Experience in machine learning, statistical methods, experimentation, model evaluation, and analytical problem solving.
Experience translating ambiguous business questions into structured analytical approaches and actionable recommendations.
Experience taking analytical work beyond analysis or model development into solutions, products, or workflows used by others.
Experience applying generative AI, LLMs, AI agents, or other emerging AI technologies to analytics, insight generation, or business workflows.
Experience with areas such as personalization, customer analytics, behavioral data, segmentation, recommendation systems, or experimentation.
Data Science IC4 - The typical base pay range for this role across the U.S. is USD $119,800 - $234,700 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 $160,200 - $261,000 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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