As a Principal Data Scientist – AI Infrastructure Data team member, 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.
In this role, you will focus on data science for AI infrastructure: turning fleet-scale telemetry, experimentation, and partner requirements into decisions that improve reliability, efficiency, capacity planning, and customer outcomes across Microsoft’s AI systems.
The AI Infrastructure team builds, operates, and optimizes one of the largest AI fleets in the world. Data Scientists use fleet-scale telemetry, experimentation, and modeling to inform infrastructure planning, systems design, product tradeoffs, and operational decisions. You will work across technical domains and partner organizations to identify the highest-impact opportunities, quantify tradeoffs, and drive action from insight to implementation.
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 Microsoft’s 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.
Data Preparation & Modeling
Acquire, clean, and prepare large datasets for modeling.
Build and deploy predictive and prescriptive models using modern machine learning techniques.
Write efficient, maintainable code and ensure scalability for production environments.
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.
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 3+ 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 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
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.
Additional or preferred qualifications:
Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 4+ 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 7+ 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 9+ 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.
#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
Data Science IC6 - The typical base pay range for this role across the U.S. is USD $165,600 - $296,400 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 $220,800 - $331,200 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.
Similar Jobs
What you need to know about the NYC Tech Scene
Key Facts About NYC Tech
- Number of Tech Workers: 549,200; 6% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Capgemini, Bloomberg, IBM, Spotify
- Key Industries: Artificial intelligence, Fintech
- Funding Landscape: $25.5 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Greycroft, Thrive Capital, Union Square Ventures, FirstMark Capital, Tiger Global Management, Tribeca Venture Partners, Insight Partners, Two Sigma Ventures
- Research Centers and Universities: Columbia University, New York University, Fordham University, CUNY, AI Now Institute, Flatiron Institute, C.N. Yang Institute for Theoretical Physics, NASA Space Radiation Laboratory
