The Time and Places team at Microsoft is at the forefront of redefining how people organize, schedule, and collaborate through intelligent calendar and meeting experiences. We build AI-powered solutions that enhance productivity-from personalized briefings and intelligent time suggestions to meeting preparation and agenda generation. Our work spans deep data science, large language model (LLM) integration, and telemetry-driven insights to deliver seamless, @context-aware user experiences across Microsoft 365. We partner closely with product, engineering, and research teams to drive innovation that scale globally and impacts millions of users daily.
The data team in Time and Places is looking for a Senior Data Scientist to join our data science team / insights and intelligence team. In this role, you will have ownership of high-visibility initiatives across our portfolio and will lead the generation of insights that drive our business. Expect to work with a host of engaged stakeholders who value your skills and consider you thought partners in driving the business!
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
Lead the design and execution of analytical frameworks to evaluate and optimize Product investments.
Partner with data scientists, product managers, and engineers to define successful metrics.
Develop dashboards and reporting pipelines to monitor feature health and experimentation outcomes, ensuring data quality and operational excellence.
Influence product strategy by translating complex data into actionable insights that inform roadmap decisions and feature prioritization.
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 stechniques 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.
1+ year experience using SQL, R or Python to implement statistical models, machine learning, and analysis (prediction, classification, clustering, time series forecasting, regression models, etc.).
Experience in stakeholder management through effective prioritization, clear communication, and delivery of actionable, data-driven insights; possesses deep expertise in A/B testing and leveraging data to guide and influence product decisions
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 working with large, distributed data sets to derive actionable insight.
Expereince in big data programming language.
Experience with experimentation design, prompt engineering, and LLM evaluation.
Experience working with Azure's analytics stack - Data Lake, Data Explorer/Kusto, Storage, Data Factory, Synapse, Data Bricks would be a plus.
Interpersonal communication and ability to leverage the data to tell a story.
Previous web analytics, product analytics and or content analytics experience.
Advanced degree in quantitative fields.
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
Microsoft will accept applications for the role until June 23, 2025.
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) .