Data Scientist II

Microsoft • Redmond, WA

13h

About The Position

The Copilot and Platform Ecosystem (CAPE) team at Microsoft is on a mission to deliver customer and partner ecosystem success through Copilot and collaborative solutions that drive measurable business value and delightful product experiences.
CAPE is hiring a Data Scientist II to join our Data & Engineering team, where we build trusted signals, metrics, and analytical foundations that power leadership reporting, Copilot experiences, and agent‑driven workflows across M365 Copilot, Copilot in Teams, and Microsoft Teams.
As a Data Scientist II, you will partner closely with data engineering, product, and engineering teams to turn large‑scale telemetry into decision‑ready insights. You will help define metrics, design experiments, evaluate outcomes, and ensure our data products are explainable, reliable, and aligned to real business questions. Your work will directly influence product direction, customer success motions, and executive decision‑making.
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
• OR Master's Degree 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 consulting experience
• OR Bachelor's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 2+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
• OR equivalent experience.
• Ability to meet Microsoft, customer and/or government security screening requirements are required for this role.
• Microsoft Cloud Background Check: This position will be required to pass the Microsoft Cloud background check upon hire/transfer and every two years thereafter.

Nice To Haves

• 2+ years of experience analyzing large datasets using SQL‑based systems and/or analytics platforms (e.g., Kusto, SQL, Spark).
• Experience designing and interpreting experiments, metrics, or analytical studies to inform product or business decisions.
• Experience communicating insights clearly through written narratives, presentations, or dashboards.
• Experience collaborating with cross‑functional partners (engineering, product, program management).
• Experience working in a data‑intensive product or platform environment, especially with telemetry or usage data at scale.
• Familiarity with Python, R, or similar languages for data analysis and modeling.
• Experience with AI/ML‑adjacent systems, evaluations, or outcome measurement (e.g., model quality, agent performance, user impact).
• Experience supporting executive‑level reporting or decision‑making.
• Exposure to cloud data platforms (e.g., Azure Data Explorer, Cosmos DB, Power BI semantic models).

Responsibilities

• Partner with data engineering, product management, and engineering to define analytical questions, success metrics, and hypotheses that drive Copilot business outcomes.
• Analyze large-scale product and customer telemetry (e.g., Kusto/ADX, Cosmos, logs, usage signals) to deliver clear, actionable insights for leaders and partner teams.
• Design and interpret experiments and evaluations (A/B tests, cohort/retention analysis, causal methods as appropriate) to measure impact of features, agents, and platform changes.
• Own and evolve core metrics and definitions (engagement, retention, adoption, quality), ensuring consistency and trust across reporting and dashboards.
• Improve data quality, freshness, and correctness by identifying gaps/anomalies and strengthening signal pipelines in partnership with data engineering.
• Build analytical models or lightweight ML to support forecasting, segmentation, classification, and outcome measurement as needed.
• Communicate complex analyses as concise narratives for technical and non-technical audiences; contribute to documentation and analytics best practices across CAPE.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: Ph.D. or professional degree