Data Scientist
Microsoft
Data Scientist
Redmond, Washington, United States
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Overview
Data Scientist – AI & Data Science Tools Team
We are seeking a pioneering, technically fluent Data Scientist to join our AI & Data Science Tools team within Microsoft Marketing’s Research + Insights organization. In this high-impact role, you’ll help shape the future of AI-powered product development and build tools that redefine how market research is done at scale.
Why Join Us?
- Be at the intersection of AI innovation and marketing strategy, influencing decisions across Microsoft.
- Drive the design, build, testing, and scaling of cutting-edge AI tools for market research.
- Enjoy high visibility and the opportunity to make a lasting impact while growing your career in one of Microsoft’s most forward-looking teams.
About the Team
Our Research + Insights team is one of the largest and most innovative market research organizations in the world, partnering closely with Microsoft’s core businesses. We thrive on tackling significant business challenges, influencing decision makers, and delivering insights that shape global strategies.
We are:
- Intellectually curious, analytical, and impact-driven.
- Passionate about data science, research excellence, and career growth.
- Committed to an open, inclusive, and transparent culture where collaboration and innovation flourish.
Qualifications
Required/minimum qualifications
- Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field OR Master's Degree 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 consulting experience
- OR Bachelor's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 2+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
- OR equivalent experience.
- Technical expertise as a developer, data scientist, or technical program manager.
- Proven experience and engagement within the AI category, building and launching generative AI solutions.
- Fluency in Python and at least one additional programming languages (example: SQL, C#, Java, R, JavaScript, Scala, Go, ReactJS etc).
- Experience leading internal change management and enablement efforts to support the adoption of new AI technologies.
Additional or preferred 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.
- Solid foundational understanding of machine learning concepts and terminology (e.g., model training, fine-tuning, embeddings, evaluation metrics).
- Comfortable collaborating closely with engineering teams and making informed trade-offs based on technical constraints and business impact.
- Ability to think strategically and envision scalable platforms, while also diving deep into edge cases, architectural decisions, and implementation details.
- Highly self-directed and effective in decentralized, fast-paced environments.
- Deep empathy for internal users and a knack for translating complex business needs into elegant and usable product experiences.
- Demonstrated ownership across the full product lifecycle: requirements gathering, technical development, testing, launch, user training, and rollout.
- Proficient analytical skills and the ability to influence decisions with data and key performance metrics.
- Outstanding verbal skills, with the ability to align and influence a wide range of stakeholders.
- Familiarity with knowledge graph technologies and semantic data modeling.
- Deep familiarity with the Azure AI tech stack.
- Ability to operate at multiple altitudes—from strategic vision to tactical execution. This includes proficiency in communication skills, both written and presentation formats.
Data Science IC3 - The typical base pay range for this role across the U.S. is USD $100,600 - $199,000 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 $131,400 - $215,400 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 October 31, 2025.
Responsibilities
- AI Graph Management: Oversee the design, development, and ongoing management of our knowledge graph architecture to support scalable AI solutions.
- Product Roadmap & Rhythm of Business (ROB): Own and evolve the product roadmap and ROB processes, ensuring alignment with strategic goals and technical feasibility.
- Cross-Functional Collaboration: Interface with developer teams, Research + Insights research managers, Marketing leadership, and partner data science teams to translate business needs into technical requirements. Technical Communication: Articulate complex technical concepts clearly to both engineering teams and executive stakeholders.
- Innovation & Execution: Drive product development in a fast-paced, ambiguous environment with a focus on delivering high-impact AI tools.