Senior Data Scientist - Media Data Science & Analytics
About The Position
We're building a Frontier Marketing organization where the Media Data Science & Analytics team leads the way in transforming how Microsoft measures, analyzes, and optimizes media investments. Our team blends advanced analytics, experimentation, and AI-powered insights to drive smarter decision-making and measurable business outcomes across paid media and owned digital properties. We operate with agility, prioritize outcomes over activity, and embrace rapid learning loops to unlock deeper audience understanding, maximize campaign impact, and accelerate innovation in media strategy. To support this transformation, we are seeking a Senior Data Scientist to help us measure the incremental impact of advertising spend and use that to help our media planning partners optimize media campaigns. Marketing data science is inherently challenging: data is often observational, incomplete, biased, or limited in scale, and outcomes unfold over time across complex systems. The successful candidate will be someone who can apply rigorous causal methods, exercise sound statistical judgment, and translate uncertainty into actionable insights that inform high-stakes investment decisions. We’re building a Frontier Marketing organization where the Media Data Science & Analytics team leads the way in transforming how Microsoft measures, analyzes, and optimizes media investments. Our team blends advanced analytics, experimentation, and AI-powered insights to drive smarter decision-making and measurable business outcomes across paid media and owned digital properties. We operate with agility, prioritize outcomes over activity, and embrace rapid learning loops to unlock deeper audience understanding, maximize campaign impact, and accelerate innovation in media strategy. To support this transformation, we are seeking a Senior Data Scientist to help us measure the incremental impact of advertising spend and use that to help our media planning partners optimize media campaigns. Marketing data science is inherently challenging: data is often observational, incomplete, biased, or limited in scale, and outcomes unfold over time across complex systems. The successful candidate will be someone who can apply rigorous causal methods, exercise sound statistical judgment, and translate uncertainty into actionable insights that inform high-stake investment decisions.
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.
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 6+ 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 8+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) OR equivalent experience.
- 5+ years’ experience building ML models.
- 5+ years’ experience writing SQL to analyze data.
- 5+ years’ experience writing code in Python.
- 3+ years’ communicating complex technical concepts to non-technical partner teams.
- 1+ years’ experience performing causal inference
- 1+ years’ experience with media / marketing data science
Responsibilities
- Design and apply causal inference approaches (e.g., quasi-experimental methods, incrementality testing, observational analysis) to estimate the true impact of media investments in settings where randomized experiments may be limited or infeasible.
- Evaluate the effectiveness of marketing strategies while explicitly accounting for data limitations, confounding, selection bias, and uncertainty.
- Translate complex causal findings into clear, decision-oriented narratives for senior marketing and business stakeholders.
- Apply advanced statistical techniques and machine learning where appropriate, with a bias toward interpretability and causal validity over purely predictive performance.
- Balance methodological rigor with pragmatism, selecting approaches that are fit for purpose given the data and business context.
- Write high-quality analytical code (Python, SQL) to support reproducible research, exploratory analysis, and ongoing measurement efforts.
- Identify opportunities to improve measurement approaches, challenge existing assumptions, and introduce best practices grounded in both academic research and industry experience.
- Prepare, validate, and analyze complex marketing datasets, identifying data quality issues, structural changes, and limitations that materially affect inference.
- Communicate data risks, constraints, and implications proactively to senior partners, ensuring conclusions are appropriately scoped and caveated.
- Uphold high standards for data ethics, privacy, and responsible use, with careful attention to how data is collected, modeled, and interpreted.
Benefits
- 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
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What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
Ph.D. or professional degree
