Data Scientist II, M365 Copilot
Reads like a ML Engineer role: putting models into production.
Redmond, WA, US
- Pay
- Pay not listedSimilar roles state $165K–$240K
- Work setting
- Not stated
- Employment
Full-time — employment source
Employment type in the employer’s posting: FULL_TIME
From the employer’s posting
What you’ll work on
Full postingDefine metrics and frameworks for evaluating LLM and agentic product performance
Experiment with models, LLMs and prompting approaches before selection
Prototype and develop AI models in containerized environments
Build and deploy basic retrieval-augmented generation workflows
Diagnose basic issues in AI/LLM systems and suggest improvements
From the employer’s posting
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
Prototypes and develops AI models using containerized environments (e.g., AI Azure Foundry, LangChain)
Develops and deploys systems for basic retrieval-augmented generation workflows
Diagnose basic issues and identifies opportunities to drive improvements within AI/LLM systems within domain area.
Tools in this posting
- Azure
Source — Tool mentions in context
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. 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 These requirements include but are not limited to the following specialized security screenings: 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.
Posting record
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- Live
- First seen by us
- Sep 26, 2026 · 33 days ago
- Recorded sightings
- 166
- Last seen by us
- Oct 30, 2026
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Job description
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. 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 These requirements include but are not limited to the following specialized security screenings: 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.
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- Location & working pattern
Redmond, WA, US
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