Senior Data Scientist, AI Infrastructure

Microsoft•Redmond, WA

6d•$142,800 - $304,200

About The Position

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.

Requirements

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.

Nice To Haves

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

Responsibilities

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.
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.
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.
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.