Senior Data Scientist - M365 Copilot, Agents & Platform - Turing Team
About The Position
Join the Microsoft Turing team to help shape enterprise and consumer productivity with Microsoft 365 Copilot. The team builds platform capabilities and AI-powered experiences used at enterprise scale. As a Senior Data Scientist, you will prepare and analyze large-scale datasets, design evaluations and experiments, and make evidence-based recommendations with measurable business impact. You will own the analytical lifecycle—from data discovery and study design through measurement and insight generation—and work in multidisciplinary teams with engineers, product managers, applied scientists, and domain experts. The role focuses on defining measurement strategies, building evaluation datasets, designing experiments, and translating results into product recommendations for AI systems and Copilot experiences. Work applies data, experimentation, and evaluation across the development lifecycle while maintaining high standards of security, quality, and trust. Project assignments may evolve according to your interests, experience, and strengths.
Requirements
- Doctorate in a listed or related field and at least 1 year of data-science experience; or a master’s degree and at least 3 years; or a bachelor’s degree and at least 5 years; or equivalent experience. Relevant experience includes managing structured and unstructured data, applying statistical techniques, and reporting results.
- Ability to meet Microsoft, customer, and/or government security screening requirements, including passing the Microsoft Cloud Background Check upon hire or transfer and every two years thereafter.
Nice To Haves
- Doctorate in a listed or related field and at least 3 years of data-science experience; or a master’s degree and at least 6 years; or a bachelor’s degree and at least 8 years; or equivalent experience.
- At least 4 years of experience using Python, SQL, KQL, R, or similar languages to analyze large-scale structured and unstructured datasets.
- Experience driving cross-organizational communication, end-to-end analytical problem solving, collaboration, customer focus, and navigating ambiguity.
- Ability to clearly communicate technical details across organizational boundaries.
- Ability to work end to end in complex analytical problem domains, from problem definition and study design through execution, interpretation, and communication of results.
- Self-driven and results-oriented, with high integrity and the ability to collaborate across disciplines, solve complex problems with diverse groups, and develop mutually beneficial solutions.
- Customer- and metrics-driven approach to evaluation, experimentation, and product decision-making.
- Demonstrated ability and motivation to learn new domains and manage ambiguity.
Responsibilities
- Prepare and analyze large-scale datasets, including customer feedback, text, and consented multimodal logs, using Python, SQL, KQL, or similar languages.
- Build representative evaluation datasets across enterprise and consumer scenarios, including retrieval, text creation and editing, image and file workflows, and various subject domains.
- Design evaluation coverage for text and voice inputs, single- and multi-turn conversations, and location- or geography-sensitive prompts.
- Partner with engineering, product management, and applied science teams to define measurement strategies and inform product decisions.
- Share findings, limitations, and recommendations to improve Microsoft 365 Copilot experiences.
- Own experiment design and impact measurement for optimization hypotheses, including success metrics, guardrails, and interpretation of results.
- Design studies and rubrics for response-quality side-by-side evaluations, analyze results, and assess statistical and practical significance.
- Compare LLM-based and human evaluations, validate alignment, investigate false positives and branding bias, and refine studies.
- Develop decision-relevant metrics, dashboards, and narratives that turn analyses into actionable product recommendations.
- Present findings and analytical limitations to technical and executive audiences, build stakeholder support, and guide decisions on product initiatives.
- Track AI offerings and competitive developments, using data and evaluation results to identify feature gaps and opportunities.
- Mentor colleagues through analytical code reviews, study-design guidance, innovation, and sharing data science best practices.
- Embody Microsoft’s culture and values.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
