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 Microsoft Planner, 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 something you are interested, we welcome your application and look forward to connecting!
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.
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.
Qualifications
Required Qualifications:
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 techn
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 tec
OR equivalent experience.
2+ years customer-facing, project-delivery experience, professional services, and/or consulting experience.
4+ years of experience leading data science and analytics projects that delivered measurable product and growth wins, including deploying AI/LLM/machine learning (ML) models to production.
4+ years of experience analyzing, visualizing, and modeling large-scale data using SQL, Python, or R.
Preferred Qualifications:
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.
Experience with A/B testing, Bayesian inference and quasi-experimental methods.
Experience building or evaluating LLM applications in production.
Data Science IC4 - The typical base pay range for this role across the U.S. is USD $119,800 - $234,700 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $158,400 - $258,000 per year.
Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here: https://careers.microsoft.com/us/en/us-corporate-pay (https://careers.microsoft.com/v2/global/en/us-corporate-pay.html)
Microsoft will accept applications for the role until July 13, 2025.
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Microsoft is an equal opportunity employer. Consistent with applicable law, all qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations (https://careers.microsoft.com/v2/global/en/accessibility.html) .
