Principal Data Scientist · Microsoft AI

Fri, 24 Apr 2026 12:16:38 GMT
Engineering

Microsoft AI · Redmond · $139,900 - $274,800 per year · hybrid

We are looking for an experienced Principal Data Scientist to join our Growth and Analytics team. As a Principal Data Scientist, you will partner with stakeholders as a trusted thought partner to drive data-informed business decisions and strategic planning. You will collaborate with cross-functional teams to define features, estimate initiative impact, and support engagement and revenue growth through analytics.

Build forecasting solutions and time-series models to project engagement, traffic, and revenue, and support scenario planning. Analyze large-scale data to identify trends, user behavior patterns, and content performance insights that improve product quality and recommendations.

Develop dashboards, reporting tools, and automated monitoring to track business health and compare actual performance against forecast. Build metric frameworks to detect anomalies, diagnose root causes, and provide timely insights when key business metrics shift.

Conduct business modeling to identify growth opportunities, evaluate trade-offs, and prioritize initiatives with solid long-term ROI. Design and analyze A/B tests to measure incremental impact, evaluate algorithm changes, and guide iterative improvements.

Apply predictive modeling, time-series analysis, and experimentation methods to improve forecasting accuracy and business performance. Communicate insights, forecasts, and recommendations clearly to technical and non-technical stakeholders to support informed decision-making.

Required Qualifications:

Doctorate 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 7+ 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 10+ years data science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)

Preferred Qualifications:

Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 8+ 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 10+ 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 12+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)

7+ years of experience in data science, statistical modeling, business analytics, forecasting, or data-driven strategy. Experience in product, web, and/or content analytics, with the ability to connect user behavior to business outcomes. Solid communication and storytelling skills, with the ability to translate complex analyses into clear business recommendations. Proven ability to manage stakeholders, prioritize effectively, and deliver actionable, data-driven insights. Experience working with large-scale event-level data and transforming raw data into metrics, dashboards, and analytical solutions using PySpark, Scala, or similar tools. Familiarity with content ecosystems, advertising, online shopping metrics, and the key drivers of engagement and monetization.