Senior Product Data Scientist

Microsoft•Redmond, WA

4d•Onsite

About The Position

Microsoft’s Path team helps customers along their journey from the initial idea to the final realization of their goals – from Idea 💡to Plan 📋to Done ✅ We are responsible for collaborative work management products including Microsoft Project, Planner, To Do, Whiteboard, and Visio. We are actively working to envision and create “The Future of Work” leveraging large language models (LLMs) and Agentic artificial intelligence (AI) to provide utility and value to our customers. As a Senior Product Data Scientist in Path you will help us measure what matters, surface actionable insights, run rigorous experiments, and help deliver transformative AI capabilities that customers love and trust. You will help drive the analysis and quality and direction of Microsoft Planner, including our agentic experiences such as Project Manager agent. In this role you will have the opportunity to apply - and advance - your data science skills and have real impact on millions of customers. This role requires Microsoft Campus presence, where you will get to interact with many of your co-workers in person. If this sounds like a great fit, we look forward to meeting you! 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. 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

Doctorate 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 Master'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 Bachelor's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 7+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
OR equivalent experience.
3+ years of experience leading data science and analytics projects that delivered measurable product and growth wins, including deploying AI/LLM/MLmodels to production.
3+ years of experience analyzing, visualizing, and modeling large-scale data using SQL, Python, or R.
3+ years of experience designing and analyzing experiments and causal inference studies.
Experience in all phases of managing data science projects including: problem definition, solution formulation, model building, productionizing and delivering measurable impact.
Experience using AI tools in data science and analytics workflows.

Responsibilities

Create customer and business impact by identifying and leading high-leverage data science and analytics opportunities across product areas.
Measurement: Define, invent, and deliver metrics which accurately measure user and business value across various products.
Experimental Design: Think critically about sampling and experimental design across User and Demand dimensions.
Product Iteration: Interpret the results of analyses, validate approaches, and learn to monitor, analyze, and iterate to continuously improve.
Cooperation: Partner effectively and drive alignment with executives, product management, engineers, and other areas of business.
Influence: engage with stakeholders to produce clear, compelling, measurable, and actionable insights and data-science driven workflows that influence product and service improvements.

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