Senior Data & Applied Scientist

Microsofts 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.

In this role 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 The work includes improving intake and triage enabling high-quality search and summarization generating draft guidance extracting insights and automate decision support into the tools and workflows that CELA professionals use every day.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.

Microsofts mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset innovate to empower others and collaborate to realize our shared goals. Each day we build on our values of respect integrity and accountability to create a culture of inclusion where everyone can thrive at work and beyond.

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.

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 Masters 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 Bachelors 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 Masters 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 Bachelors 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 decisions amid ambiguity collaborate across legal policy research product and engineering disciplines manage competing constraints and deliver high-quality results.

Data Science IC4 - The typical base pay range for this role across the U.S. is USD $119800 - $234700 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 $160200 - $261000 per year.

Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:
position will be open for a minimum of 5 days with applications accepted on an ongoing basis until the position is filled.

Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age ancestry citizenship color family or medical care leave gender identity or expression genetic information immigration status marital status medical condition national origin physical or mental disability political affiliation protected veteran or military status race ethnicity religion sex (including pregnancy) sexual orientation or any other characteristic protected by applicable local laws regulations and ordinances. If you need assistance with religious accommodations and/or a reasonable accommodation due to a disability during the application process read more about requesting accommodations.

Required Experience:

IC