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 and digital experiences. 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 impact, and accelerate innovation in media and discovery strategy.

To support this transformation, we are seeking a Senior Data Scientist to lead advanced experimentation and causal inference efforts that enable rigorous campaign measurement and drive data-informed marketing decisions at scale. In this role, you'll directly support Microsoft's mission by enabling data-driven marketing decisions that drive customer engagement and revenue growth. Shape What You Will Do As a Senior Data Scientist on the Media Data Science and Analytics team, you will design and implement advanced experimentation frameworks including Bayesian hypothesis testing, causal inference modeling, and heterogeneous treatment effect analysis, while building and deploying Machine Learning (ML) models and data pipelines to support portfolio impact measurement and campaign analytics at scale. This will include developing solutions that are reusable, readily discoverable by decision makers, and self-service oriented, driving meaningful interpretation of data, and supporting campaign optimization.

This candidate thrives in fast-paced environments, demonstrates comfort with ambiguity, and collaborates effectively across teams and functional boundaries. Curiosity, a bias for action, and the ability to balance business context with technical experience are essential. In this role, you will support the rhythm of business by providing actionable recommendations to stakeholders based on rigorous analysis and clear insights. You will leverage statistical and machine learning techniques to develop scalable, efficient, and impactful data products while also diving deep into the details to uncover the story behind the data. You will bring sharp analytical thinking, communication skills, and the confidence to engage with executives and stakeholders across 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.

In alignment with our Microsoft values, we are committed to cultivating an inclusive work environment for all employees to positively impact our culture every day.

• Experimentation and Causal Inference Design and implement advanced experimentation frameworks including Bayesian hypothesis testing and causal inference modeling.
• Develop heterogeneous treatment effect analyses to understand differential campaign impacts across customer segments.
• Establish clear linkage between A/B test results and desired business outcomes.
• Assess the degree to which campaigns meet business objectives and address gaps.
• Ensure alignment on definitions and standards across stakeholders.
• Define, design, and promote appropriate feedback and evaluation methods. Present results and findings to senior stakeholders.
• Build and deploy ML models to support portfolio impact measurement and campaign analytics at scale.
• Develop and maintain data pipelines that enable scalable, automated analysis.
• Evaluate the viability of automated methods for data collection, reporting, and analysis.
• Ensure solutions are reusable, easily discoverable, and self-service oriented.
• Identify and promote methods that enhance efficiency in analytics and reporting.
• Drive meaningful data interpretation to inform business decisions and shape organizational understanding through compelling storytelling.
• Recommend and socialize optimal methods for operationalizing, sharing, and scaling insights.
• Share knowledge and practical rationale for transitioning ad-hoc analyses to regular reporting features.
• Share domain knowledge to create clarity and ensure readiness to leverage data and insights effectively.
• Orchestration and Collaboration Leverage working relationships within and across teams to ensure alignment and quality execution.
• Drive the adoption of recommended data sources and analysis practices.
• Consult across teams and influence data strategy, experimentation culture, and measurement frameworks on decisions related to data sourcing, analyses, and interpretation of results.
• Coach and mentor less experienced analysts, as needed, and enable cross-functional partners to become data-savvy.
• Share insights and analytical experience through various means, including dashboards, reports, and visualizations.
• Synthesize and simplify details across analyses to highlight relevant findings. Identify opportunities to improve the efficiency of insights reporting techniques.
• Guide others and establish partnerships with stakeholders to ensure results are accessible and relevant.
• Embody our Culture and Values

Required/minimum qualifications

• Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 1+ year(s) experience in data science, applied statistics, machine learning, or quantitative research
• OR Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 3+ years experience in data science, applied statistics, machine learning, or quantitative research
• OR Bachelor's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 5+ years experience in data science, applied statistics, machine learning, or quantitative research
• OR equivalent experience.

Additional or preferred qualifications

• Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 3+ years experience in data science, applied statistics, machine learning, or quantitative research
• OR Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 5+ years experience in data science, applied statistics, machine learning, or quantitative research
• OR Bachelor's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 7+ years experience in data science, applied statistics, machine learning, or quantitative research
• OR equivalent experience.

• 4+ years of experience with Python or R for statistical analysis and machine learning.
• 4+ years of experience with SQL and data pipeline development.
• 3+ years of experience designing and analyzing A/B experiments or causal inference studies.
• 2+ years of experience with Bayesian methods, causal inference techniques (e.g., difference-in-differences, instrumental variables, propensity score matching), or heterogeneous treatment effect estimation.
• 2+ years of experience building and deploying ML models.
• 4+ years of experience presenting complex technical findings to both technical and non-technical senior level stakeholders.
• Experience with marketing mix modeling (MMM) or attribution modeling.
• Experience with cloud-based ML platforms (e.g., Azure ML, Databricks).
• 4+ years' experience analyzing marketing campaign performance.
• Experience with Microsoft Fabric, Power BI, or similar visualization platforms.

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.