# Senior Data & Applied Scientist Source: https://realanalystjobs.com/job/senior-data-and-applied-scientist-microsoft-38c712c7 Senior Data & Applied Scientist at Microsoft, an on-site role based in Redmond, Washington, USA. Experience level: 1+ Years. Posted on 13 November 2026, read from Microsoft's own careers page (Eightfold), which RealAnalystJobs re-checks daily and removes the role when it closes. Microsoft has approved H-1B petitions on USCIS record (employer-wide, not a promise for this role). Updated 15 November 2026. ## Key facts - Company: [Microsoft](https://realanalystjobs.com/companies/microsoft) - Location: Redmond, Washington, USA - Work mode: On-site - Posted: Nov 13, 2026 - Employment type: Full time - Experience level: 1+ Years - Source: Microsoft's careers page (Eightfold), re-checked daily Skills: [SQL](https://realanalystjobs.com/skills/sql), [Python](https://realanalystjobs.com/skills/python), [R](https://realanalystjobs.com/skills/r) ## Visa sponsorship The posting does not say. Microsoft had H-1B petitions approved for 3,828 workers in fiscal year 2026 (USCIS). That is history, not a promise for this role. [See the record](https://realanalystjobs.com/companies/microsoft#h1b-record) ## About this role Overview Microsoft's AI for CELA team is part of Corporate, External, and Legal Affairs (CELA), the organization that brings together legal, regulatory, public policy, compliance, and corporate affairs professionals to help Microsoft navigate complex issues and operate responsibly. The team is seeking a Senior Data & Applied Scientist to apply advanced data science, machine learning, and artificial intelligence to transform how these professionals capture knowledge, manage work, and respond to a rapidly changing regulatory environment. This role is aligned to the Data Science IC4 career stage. You will identify and frame complex, ambiguous problems; create project plans that account for risks, constraints, assumptions, and available resources; and connect technical measures to meaningful outcomes for legal professionals, business clients, and engineering teams. You will build AI-enabled knowledge-management capabilities that convert fragmented requests, guidance, communications, and work product into structured, governed, and reusable institutional knowledge. The work includes improving intake and triage, enabling high-quality search and summarization, generating draft guidance, extracting insights, and automate decision support into the tools and workflows that CELA professionals use every day. You will also develop AI solutions for continuous regulatory intelligence, including 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 requires strong technical judgment, partnership with legal and regulatory experts, disciplined evaluation, human-in-the-loop design, clear communication, and a commitment to responsible, secure, and auditable AI. Responsibilities • Own complex data science engagements by translating ambiguous legal, knowledge-management, and regulatory problems into clear objectives, project plans, measurable success criteria, and roadmaps that improve outcomes over time. • 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 that connect technical performance to accuracy, consistency, traceability, adoption, capacity returned, and business value, while ensuring that legal and regulatory judgment remains with accountable experts. • Build trusted 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 across the team. Qualifications Required 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. Preferred Qualifications • 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 6+ 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 8+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) OR equivalent experience. • Advanced knowledge of statistical analysis, experimentation, algorithms, machine learning, and AI, with experience 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 the definition of quality and impact metrics. • Demonstrated ability to own complex projects, make sound de Description from Microsoft's public careers feed, reproduced so you can read the role here. Apply on the company's own site; Real Analyst Jobs never submits anything for you. ## How to apply Open [this role on Real Analyst Jobs](https://realanalystjobs.com/job/senior-data-and-applied-scientist-microsoft-38c712c7) and use Apply now there to reach the employer's application. The listing is re-checked against Microsoft's careers page daily and removed when it closes. ## Microsoft 8 open analyst roles on Real Analyst Jobs. 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