Data Scientist II, M365 Copilot

Microsoft•Redmond, WA

4d•$102,100 - $202,200

About The Position

Come build the core of Microsoft Copilot for enterprise with Microsoft Turing Team, where you'll join a collaborative group of applied scientists and engineers pushing the frontier of large language models (LLMs) to improve the productivity of hundreds of millions of users around the world. Our team is responsible for the core systems that power Microsoft 365 Copilot Chat delivering intelligence, quality, and transformative new features. We work at the intersection of research and engineering—advancing orchestrator reasoning, training next-generation models, and shipping impactful, model-driven experiences in Microsoft 365 Copilot. As a Data Scientist II - M365 Copilot, you will: - Build and deliver model-driven features from concept to production - spanning model development, evaluation, metrics, and A/B testing- Evolve our orchestrator to reason more effectively, respond faster, and support new capabilities in multi-modality, agent-based systems, and beyond. We’re hiring a Data Scientist II who is passionate about deep learning, NLP, multimodality model, and model optimization. Come build the next generation of AI with us. 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

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 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 Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field OR equivalent experience.
Ability to meet Microsoft, customer and/or government security screening requirements are required for this role.
These requirements include but are not limited to the following specialized security screenings: 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

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 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) 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 equivalent experience.

Responsibilities

Build and deliver model-driven features from concept to production - spanning model development, evaluation, metrics, and A/B testing
Evolve our orchestrator to reason more effectively, respond faster, and support new capabilities in multi-modality, agent-based systems, and beyond.
Collaborates with immediate team members on defining metrics and frameworks for evaluating somewhat complex AI/large language model (LLM) systems and agentic product performance.
Experiments with model before selection (e.g., LLM, prompting approach) for tasks within a product or solution
Diagnose basic issues and identifies opportunities to drive improvements within AI/LLM systems within domain area.
Prototypes and develops AI models using containerized environments (e.g., AI Azure Foundry, LangChain) to operationalize, build, and validate scalable tools/applications/solutions for use by the immediate team.
Develops and deploys systems for basic retrieval-augmented generation workflows, assisting in the selection of data sources, retrieval systems, and generative models to ensure quality output.
Assists senior members in assessing and refining LLM systems and models.