Senior Data Scientist

MicrosoftRedmond, WA
2h

About The Position

Join us at the forefront of innovation in Microsoft Copilot Studio's COO Data Science team within the Business Industry Copilot organization, where data-driven insights and intelligent experimentation power product-led growth. As a Senior Data Scientist, you will own end-to-end analytics and machine learning solutions that shape how customers build, deploy, and use copilots and AI agents. You will partner closely with product managers, engineers, and business stakeholders to design experiments, build production models, and extract actionable insights that accelerate product adoption, improve agent performance, and influence Microsoft Copilot Studio's growth strategy. This role is ideal for someone who thrives at the intersection of analytics, experimentation, and ML engineering, and enjoys turning ambiguous product questions into measurable business impact. 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.
  • 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

  • Experience driving product-led growth, optimizing user journeys, or developing insights that drive product adoption or revenue / cost outcomes.
  • Hands-on experience building or evaluating AI agents, copilots, or LLM-powered systems, including working with agent workflows, prompt engineering, tool-calling, or evaluation metrics for agent performance.
  • Experience with experimentation (A/B testing, causal inference, metric development).
  • Experience working with large-scale datasets in distributed or cloud environments (e.g. Kusto/Azure Data Explorer, Spark, Fabric, or similar).
  • Strong engineering skills: ability to build pipelines, automate analyses, and work with production data systems.
  • Knowledge of evaluation systems, including prompt/agent performance measurement, regression testing, or automated evaluation framework.
  • Experience building, deploying, or monitoring ML models in production (e.g. Azure ML, ML flow, CI/CD for ML).
  • Experience with generative AI, LLMs, prompt optimization, or agentic reasoning systems is a plus.
  • Excellent collaboration and communication skills across cross-functional partners.
  • Professional experience writing SQL or Kusto queries to analyze large-scale datasets.
  • Hands-on experience building or evaluating machine learning models using Python or R.
  • Conducted or analyzed A/B tests, controlled experiments, or other statistical experimentation methods in a previous role.
  • Worked with data in a cloud or distributed environment (e.g. Azure, AWS, Spark, or similar).

Responsibilities

  • Lead analytics insights: perform deep quantitative analysis and exploratory data work to identify trends, diagnose user behaviors, surface actionable insights, and guide product-led growth strategies.
  • Build intelligent solutions: Design, develop, and productionize ML models, AI agents, and other AI-driven heuristics (e.g. quality evaluation, forecasting, scoring) that improve product performance and influence roadmap prioritization.
  • Drive experimentation: Design, implement, and analyze A/B tests and other experimental methods to validate hypotheses and optimize Copilot Studio experiences at scale.
  • Partner for impact: Collaborate with PM, engineering, and research partners to define metrics, measure success, and drive data-informed decision making across Copilot Studio.
  • Operationalize ML: Implement evaluation pipelines, monitoring, and model performance tracking for production workloads, ensuring security, reliability, robustness, and responsible AI standards.
  • Communicate with clarity: Share insights and recommendations with senior leaders and cross-functional stakeholders to align strategy and accelerate business outcomes.
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