As a Senior Data Scientist, you will own end-to-end delivery of strategic data science projects and partner with customers and internal teams to design and implement advanced analytics and AI solutions that create measurable business impact. This hands on role blends deep technical expertise with consulting and stakeholder engagement, enabling you to influence decisions and guide adoption of data-driven strategies.
The AI Infrastructure team builds, operates and optimizes one of the largest AI fleets in the world. Our Data Scientists leverage data to inform everything from infrastructure planning to systems design to product feature tradeoffs. You will be expected to work across a wide variety of subject matters and partnership levels to identify and drive action against the largest opportunities.
The AI Infrastructure Data team is full stack owning telemetry collection, data infrastructure, processing, experimentation and measurement for a wide range of partner teams, systems and business processes. Close collaboration with Data Engineers, Data Infrastructure SWE and SMEs are a day to day component of our model. The team regularly interacts with hyperscale datasets, systems and challenges to deliver impact to the companies most important initiatives.
At Microsoft, our mission to empower every person and every organization on the planet to achieve more guides how we partner with customers to deliver trusted, impactful solutions. With a growth mindset culture, we innovate responsibly and measure success by shared progress people, teams, and customers. Join us to do meaningful work that changes the world and helps shape what’s next for everyone.
Responsibilities
Business Understanding & Impact
Own delivery of complex, high-impact data science and AI solutions for strategic consulting engagements.
Collaborate with stakeholders to define business problems and translate them into actionable AI-driven solutions.
Develop project plans, assess risks, and ensure alignment with strategic objectives and ethical AI principles.
Identify opportunities to leverage generative AI for business transformation and innovation.
Data Preparation & Modeling
Acquire, clean, and prepare large datasets for modeling.
Build and deploy predictive and prescriptive models using modern machine learning techniques.
Design, develop, and integrate generative AI applications (e.g., text, image, multimodal) into client workflows and solutions.
Write efficient, maintainable code and ensure scalability for production environments.
Implement prompt engineering, fine-tuning, and evaluation strategies for large language models and other foundation models.
Insight, Communication & Enablement
Present findings to senior stakeholders using compelling storytelling and visualizations.
Simplify complex ML/AI concepts for diverse audiences to drive understanding and adoption.
Document best practices for AI application development and share knowledge across teams.
Collaboration & Consulting
Act as a trusted advisor to internal teams and customers, ensuring solutions meet business needs.
Promote responsible AI practices, including fairness, transparency, and explainability in model and application development.
Stay current with emerging AI technologies, frameworks, and tools to continuously enhance solution capabilities.
Qualifications
Required/minimum 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.
Additional or 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.
Proven consulting and stakeholder engagement skills with proven ability to influence decisions.
Proficiency in Python and SQL; experience with cloud platforms (Azure preferred).
Knowledge of Responsible AI principles and ethical data practices.
Experience with broader software engineering lifecycle practices, including version control, testing, DevOps, and production deployment of Machine Learning (ML) solutions.
Experience with AI-assisted coding practices and specification-driven development.
1 to 3 years of Consulting (including System Integrator, Technical Consulting or Management Consulting) experience.
Experience developing and deploying Agentic AI solutions
#AIinfra
Data Science IC5 - The typical base pay range for this role across the U.S. is USD $142,800 - $274,800 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 $188,000 - $304,200 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.
Skills Required
- Degree in Data Science, Mathematics, Statistics, Economics, OR Computer Science with required years of data-science experience (Doctorate+1 year, Master's+3 years, Bachelor's+5 years) or equivalent experience
- Experience managing structured and unstructured data, applying statistical techniques, and reporting results
- Proficiency in Python
- Proficiency in SQL
- Experience with cloud platforms (Azure preferred)
- Proven consulting and stakeholder engagement skills with ability to influence decisions
- Knowledge of Responsible AI principles and ethical data practices
- Experience with software engineering lifecycle practices (version control, testing, DevOps, production ML deployment)
- Experience with AI-assisted coding practices and specification-driven development
- 1 to 3 years consulting experience (system integrator, technical consulting, or management consulting)
- Experience developing and deploying Agentic AI solutions
Microsoft Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Microsoft and has not been reviewed or approved by Microsoft.
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Fair & Transparent Compensation — Pay is presented as broadly competitive overall, with clear role/level/location variation and an emphasis on using posted ranges and band information for apples-to-apples comparisons.
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Retirement Support — Retirement benefits are described as a standout, highlighted by a strong 401(k) match structure and immediate vesting, plus additional plan features for tax-advantaged saving.
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Parental & Family Support — Family-oriented benefits are portrayed as a meaningful strength, with substantial paid parental leave and added supports like back-up care and adoption/surrogacy assistance.
Microsoft Insights
What We Do
At Microsoft, our mission is to empower every person and every organization on the planet to achieve more. Our mission is grounded in both the world in which we live and the future we strive to create. Today, we live in a mobile-first, cloud-first world, and the transformation we are driving across our businesses is designed to enable Microsoft and our customers to thrive in this world.
