Senior Data & Applied Scientist

Microsoft • Redmond, WA

1d • $119,800 - $261,000

About The Position

Microsoft's AI for CELA team is part of Corporate, External, and Legal Affairs, which brings together legal, regulatory, public policy, compliance, and corporate affairs professionals. The team seeks a Senior Data & Applied Scientist to use advanced data science, machine learning, and artificial intelligence to improve how these professionals capture knowledge, manage work, and respond to regulatory change. The role is aligned to the Data Science IC4 career stage and involves framing complex, ambiguous problems, planning projects around risks and constraints, and connecting technical measures to meaningful outcomes for legal professionals, business clients, and engineering teams.

The scientist will build AI-enabled knowledge-management capabilities that turn fragmented requests, guidance, communications, and work product into structured, governed, reusable institutional knowledge. This includes improving intake and triage, search and summarization, draft guidance, insight extraction, and decision support within CELA tools and workflows. The role will also develop AI solutions for continuous regulatory intelligence: detecting and prioritizing regulatory changes, extracting and structuring requirements, mapping changes to obligations, policies, products, and controls, and producing traceable impact assessments for expert review. Success depends on sound technical judgment, collaboration with legal and regulatory experts, disciplined evaluation, human-in-the-loop design, clear communication, and responsible, secure, auditable AI.

Requirements

• Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or a related field and at least 1 year of data-science experience; or a master's degree in one of these fields and at least 3 years of experience; or a bachelor's degree in one of these fields and at least 5 years of experience; or equivalent experience.
• Experience managing structured and unstructured data, applying statistical techniques, and reporting results.
• Advanced knowledge of statistical analysis, experimentation, algorithms, machine learning, and AI, including selecting and applying methods appropriate to the problem, data, and desired outcome.
• Experience managing, transforming, and analyzing structured and unstructured data and developing reproducible solutions using SQL or related query languages and Python, R, or another relevant programming language.
• Experience developing, evaluating, or operationalizing scalable machine learning or AI systems, including retrieval, natural language processing, large language models, agentic workflows, and defining quality and impact metrics.
• Ability to own complex projects, make sound decisions amid ambiguity, collaborate across legal, policy, research, product, and engineering disciplines, manage competing constraints, and deliver high-quality results.
• Excellent written, verbal, storytelling, and technical communication skills, including presenting findings to senior technical and non-technical stakeholders and mentoring practitioners.

Nice To Haves

• Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or a related field and at least 3 years of data-science experience; or a master's degree in one of these fields and at least 6 years of experience; or a bachelor's degree in one of these fields and at least 8 years of experience; or equivalent experience.

Responsibilities

• Own complex data science engagements by turning ambiguous legal, knowledge-management, and regulatory problems into objectives, project plans, measurable success criteria, and roadmaps.
• Acquire, assess, and prepare structured and unstructured data from communications, documents, matters, regulatory sources, and operational systems; identify data-quality, integrity, privacy, security, bias, and ethical risks; and establish reliable data foundations for AI.
• Design, develop, and evaluate statistical, machine learning, and generative AI approaches for classification, routing, retrieval, summarization, knowledge drafting, metadata extraction, regulatory monitoring, requirements extraction, and impact analysis.
• Write efficient, readable, extensible, production-quality analysis and software code; diagnose complex issues; prototype and operationalize scalable solutions; and partner with engineering teams on deployment, monitoring, maintenance, and continuous improvement.
• Define evaluation metrics and human-review workflows linking technical performance to accuracy, consistency, traceability, adoption, capacity returned, and business value, while ensuring legal and regulatory judgment remains with accountable experts.
• Build partnerships with legal professionals, policy experts, engineers, researchers, and business stakeholders; influence decisions through clear narratives and visualizations; mentor less experienced practitioners; and establish responsible AI, data, and engineering best practices.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior