Senior Data Scientist at Microsoft

Redmond, Washington, United States -

Full Time

Start Date

Immediate

Expiry Date

16 May, 26

Salary

234700.0

Posted On

15 Feb, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Analysis, Modeling, SQL, R, Python, LLMs, AI Technologies, Statistical Techniques, Machine Learning, Evaluation Frameworks, Data Science Strategy, Product Road Map Influence, Data Pipelines, ML Workflows, Cosmos DB, Azure

Industry

Software Development

Description

Overview Do you want to be at the cutting edge of AI that expands SharePoint’s role as a leader in content management as we enter the age of AI. The SharePoint Platform powers file collaboration for OneDrive, Microsoft Office, Teams, OneNote, Education, Copilot, and much more – making it one of the largest storage platforms in the world and a leader in content management systems. This storage is at the heart of AI, powering Copilot experiences across Microsoft 365. We’re looking for a Senior Data Scientist with an understanding complex platform problems and using industry-leading analytical techniques to find insights that transform our business and product experiences. Ideal candidates should be able to take a business or engineering problem from Product, Applied Science or Engineering leaders, translate it to a Data Science problem, conduct the appropriate analysis and modeling to reveal actionable insights, and help drive deep change. As a Senior Data Scientist for the OneDrive and SharePoint Platform team, you will shape the future of AI across Microsoft 365 by leading the innovation and delivery of the core OneDrive and SharePoint AI Platform. You will drive the data science vision and strategy for the team, which is the backbone of Microsoft 365 AI experiences, and provides foundational file grounding and RAG across all Microsoft products and services. You will help develop deep understanding of how the SharePoint platforms enables and empower core AI scenarios for Copilot, Agents, Copilot Notebooks and many Microsoft applications. You will be part of a high-performing and high-ambition Product Management organization for one of the largest and most impactful services on the planet, which provides the essential storage and data that fuels AI and Copilot scenarios. You will foster a culture of data obsession, innovation, and collaboration within our team and across Microsoft. We are a modern team of product managers, applied scientists and engineers for one of the largest business and consumer services on the planet. Our product ranges from consumer mobile features to developer experiences to large-scale distributed systems. We are data informed and hypothesis driven and measure our outcomes to prove we deliver value to customers. We partner closely with a talented and senior set of engineers, designers, and researchers. Most of our team is local to Redmond, Washington. We also work with peers in Europe & Asia and we all contribute directly to OneDrive & SharePoint. Part of building a successful team is having an inclusive workplace where all people and ideas are welcome. Transparency is also core to our culture. We leverage internal & external tools to get feedback, celebrate the work of our peers, and drive local and industry level changes. Additionally, we believe strongly in providing new opportunities for talent mobility & experimentation in your job with other parts of the team and company. Lastly, we focus on, and have a track record of, delivering strong business results with key metrics to track our successes and failures. We like to have fun, celebrate our wins, and learn from our mistakes. 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 Work across different functions to translate business problems into ones that can be solved and informed by data analysis. Have curiosity and apply analytical skills to dive deep into data to find key insights that identify platform problems and potential solutions. Develop models of platform usage, user behavior & business behavior to make recommendations and influence the product road map. Develop and apply rigorous evaluation frameworks, including inventing new metrics and validation methods as needed. Maintain deep industry knowledge of data science trends and technologies to inform strategy and thought leadership. Prepare clear executive-ready reviews, including presentations and asynchronous communications. Build, maintain, and report scorecards to track quality, performance, and business outcomes. Partner with Applied Science & Research, as well as your peers in PM across Microsoft to deliver seamless platform capabilities. Utilize tools like SQL, R, Python to execute analyses. Utilize LLMs and other AI technologies to revolutionize data science practices within the team, enhancing the speed, accuracy, and scalability of data analysis and insight generation. Embody our culture and values 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 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. Other Requirements: 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. 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. Advanced degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field with deep, sustained data science experience. Experience managing complex structured and unstructured datasets and applying advanced statistical or machine learning techniques. Experience designing and optimizing data models and queries in Cosmos DB at scale. Experience deploying and monitoring ML models in Azure-based production environments. Experience defining evaluation methodologies and influencing data science standards at team or organizational level. Experience working with large-scale, distributed data stores. Experience programming skills in Python or C# with experience building data pipelines and production ML workflows. 2+ years’ experience working in enterprise software and large-scale platforms, project-delivery experience, professional services, and/or consulting experience. 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 This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled. Microsoft is an equal opportunity employer. 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 with religious accommodations and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.

Responsibilities

The role involves translating complex business or engineering problems into solvable Data Science problems, conducting analysis and modeling to reveal actionable insights, and driving deep change across the OneDrive and SharePoint AI Platform. Responsibilities include developing models of platform usage, creating rigorous evaluation frameworks, and utilizing tools like SQL, R, and Python to execute analyses.