The Senior Data & Applied Scientist role at Global Skilling focuses on driving product and program analytics for Microsoft's skilling experiences. The team aims to enhance personalized learning experiences through data insights and statistical methods. The position involves collaborating with various teams to improve user experiences and accelerate learner proficiency. Candidates should be passionate about AI skilling and data-driven decision-making.

• Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 1+ year(s) data-science experience OR
• Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 3+ years data-science experience OR
• Bachelor's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 5+ years data-science experience OR
• Equivalent experience.
• 4+ years of experience in data science, product/journey analytics, causal inference, and user behavioral modeling is preferred.

• Own product/program analytics and insights for Microsoft skilling experiences to drive product/program strategy and improve the end-to-end learner experience.
• Design and analyze learner journeys and funnels to understand behavior across discovery, engagement, completion, and retention.
• Define and operationalize product/program success metrics and content quality/relevance metrics.
• Build measurement frameworks and new metrics to quantify learner proficiency and skill growth.
• Conduct deep-dive analyses to identify drivers of engagement, proficiency, and retention.
• Plan and evaluate experiments and causal analyses to measure the impact of new features and changes.
• Set up operating rhythms to ensure insights consistently influence product decisions.
• Partner with Engineering and Product/Program Management to shape product telemetry and data instrumentation.
• Develop, operationalize, and evolve competency models and skill taxonomies.
• Evaluate the effectiveness of learning content and curriculum through causal analysis.
• Identify which content and learning assets drive the highest retention and success.
• Use behavioral signals and multi-modal modeling to recommend improvements to content strategy.
• Mentor other data scientists and review analyses to maintain high analytical rigor.
• Ensure telemetry and analyses meet user privacy and consent expectations.

• Employees at Microsoft are often offered comprehensive, “world-class” benefits—including health and mental-wellness programs, competitive pay with bonuses and stock awards, and retirement/savings options. Time-off and flexibility are common, with generous vacation and holidays, parental and caregiver leave, and flexible work schedules, alongside learning support, employee resource groups, product discounts, and matching-gifts/volunteering programs. Specific benefits can vary by region.