Senior Data & Applied Scientist

Microsoft

13h

About The Position

At Global Skilling, our mission is to inspire every person and organization on the planet to reach their potential through learning. As technology evolves rapidly, having a skilled workforce is more important than ever. We believe making learning accessible to all is key to fostering a diverse and inclusive culture, helping people excel personally and professionally, and igniting innovation. Are you passionate about AI skilling and using data to build delightful, personalized learning experiences? Do you get excited about exploring new datasets, identifying industry trends, and translating insights into product improvements? Come join the Global Skilling Data Science team. We are hiring a Senior Data Scientist to drive product/program analytics and insights for Microsoft skilling experience, including AI Skills Navigator, a new agentic learning experience designed to help learners discover the right skills, choose the right learning paths, and accelerate proficiency. The Senior Data & Applied Scientist brings product/program analytics experience, including customer journey and funnel analytics, causal measurement, and experimentation frameworks. In this role, you will leverage statistical methods and data storytelling to understand learner behavior, identify opportunities, and develop metrics that measure product performance and learning outcomes. You will work closely with Product Management and Engineering to shape product telemetry and data foundations, and you will partner across Design, User Research, Sales, Marketing, and Finance to deliver insights that inform product strategy, improve user experiences, close skill gaps, and accelerate learner proficiency. As part of our team, you will thrive while working with a variety of technologies (not limited to Microsoft technology). You will solve meaningful business problems, contribute to open source where appropriate, and collaborate with partner teams across Microsoft. Microsoft’s 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.

Requirements

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.

Nice To Haves

4+ years of experience in data science, product/journey analytics, causal inference, and user behavioral modeling.
Experience driving product improvements through data and insights.
Proficiency in Python, R, SQL, KQL, PySpark, and modern analytics frameworks.
Experience designing experiments, defining standardized metrics, performing causal analyses, and delivering behavior-driven insights.
Experience with learning platforms and/or learner competency and skill modeling (e.g., proficiency, mastery, and skill signals).
Experience levering AI to deliver accelerate time to insight and depth of insights
Hands-on experience with large-scale enterprise data platforms (e.g., Fabric, Synapse, ADX, Delta Lake, ADF, Databricks, Snowflake).

Responsibilities

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 (north star, input metrics, and guardrails), and content quality/relevance metrics. Conduct data quality checks.
Build measurement frameworks and new metrics to quantify learner proficiency and skill growth (e.g., consumption signals, certifications, and expertise indicators).
Conduct deep-dive analyses to identify drivers of engagement, proficiency, and retention; surface opportunities and risks.
Plan and evaluate experiments (A/B tests) and causal analyses to measure impact of new features and changes; communicate actionable recommendations.
Set up operating rhythms (weekly business review metrics, experiment readouts, KPI health dashboards) so insights consistently change product decisions.
Partner with Engineering and Product/Program Management to shape product telemetry, data instrumentation, and scalable reporting to enable self-serve insights.
Develop, operationalize, and evolve competency models, skill taxonomies, and certification readiness frameworks to measure proficiency progression and mastery.
Evaluate the effectiveness of learning content and curriculum through causal analysis, sequential behavior signals, and outcome-based performance.
Identify which content, modalities, and learning assets drive the highest retention, mastery, certification success, and deployment readiness.
Use behavioral signals and multi-modal modeling to recommend improvements to content strategy, learning design, and curriculum sequencing.
Mentor other data scientists, review analyses, set a high bar for analytical rigor.
Ensure telemetry and analyses meet user privacy, consent, retention expectations

Benefits

Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here: https://careers.microsoft.com/us/en/us-corporate-pay

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