[Hiring] Principal Data Scientist - AI Infrastructure @Microsoft

Role Description

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.
• Working across technical domains and partner organizations to identify the highest-impact opportunities, quantify tradeoffs, and drive action from insight to implementation.

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.

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. 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

• Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 3+ years data-science experience.
• OR Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 5+ years data-science experience.
• OR Bachelor's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 7+ years data-science experience.
• OR equivalent experience.

Requirements

• Ability to meet Microsoft, customer and/or government security screening requirements.
• 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.

Benefits

• The typical base pay range for this role across the U.S. is USD $142,800 - $274,800 per year.
• The typical base pay range for this role in the San Francisco Bay area and New York City metropolitan area is USD $188,000 - $304,200 per year.
• Data Science IC6 - The typical base pay range for this role across the U.S. is USD $165,600 - $296,400 per year.
• The typical base pay range for this role in the San Francisco Bay area and New York City metropolitan area is USD $220,800 - $331,200 per year.
• Certain roles may be eligible for benefits and other compensation.