Microsoft’s objective is to enable every individual and organization globally to realize their fullest potential. As part of the AX&E Product org, we are seeking a Senior Data Scientist to lead high-impact initiatives that drive insights and innovation across our technical communities and product ecosystems.
This role is ideal for someone who thrives in a fast-paced environment, enjoys solving complex problems, and is passionate about using data to influence product strategy and customer experience. You will work closely with cross-functional teams including PMs, engineers, and business stakeholders to deliver actionable insights and scalable data solutions.
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.

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.
• 5+ years of experience in data science, analytics, or machine learning.
• 3+ years of programming skills in Python, R, or equivalent.
• 3+ years proficiency in Structured Query Language (SQL) and experience with big data technologies (Spark, Azure Data Lake, Kusto, etc.).
• 3+ years experience with cloud-based analytics platforms (Azure, Synapse, Data Factory, etc.).

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 3+ years 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 5+ 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 7+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
• OR equivalent experience.
• 1+ year(s) experience with web analytics and telemetry data, along with familiarity with the Azure portal and Azure revenue, is preferred.
• 1+ year(s) of demonstrated ability to lead projects independently and influence cross-functional teams, supported by strong stakeholder management and communication skills.
• 1+ year(s) of comfortability with working in ambiguous and evolving environments, with a growth mindset and passion for continuous learning.
• 1+ year(s) of skills synthesizing complex problems into actionable insights and telling compelling stories using data.

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 $158,400 - $258,000 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
Microsoft will accept applications for the role until September, 11, 2025

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Microsoft is an equal opportunity employer. Consistent with applicable law, 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 and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations

• Design and build efficient data pipelines to ingest and process large-scale telemetry with high reliability and low latency.
• Architect data models and systems that ensure data integrity, scalability, and responsiveness.
• Partner with stakeholders to define and execute critical insights for business decision-making.
• Apply statistical and machine learning techniques to identify trends, forecast outcomes, and detect anomalies.
• Build predictive models and recommendation systems using advanced Machine Learning (ML) techniques.
• Foster strong relationships across engineering, product, and data science teams, while mentoring other data scientists and contributing to a culture of data-driven decision-making.
• Communicate complex findings clearly to technical and non-technical audiences.