Senior Data Scientist - Consumer Marketing

The Digital Direct Sales Reporting, Analytics, and Data Science team is hiring a Senior Data Scientist - Consumer Marketing to help advance personalization and decision science. This role will contribute deep expertise in large-scale user segmentation, experimentation, and AI-enabled decisioning, with a particular focus on marketing and ecommerce applications across website and outbound channels. This role operates with broad technical influence, cross-functional collaboration, and end-to-end accountability for measurable business outcomes.

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 positivelyimpactour culture every day.

• Define and lead the technical strategy for causal modeling & virtual experimentation approaches (simulation, synthetic controls/data generation where appropriate) to de-risk decisions and accelerate learning.
• Collaborate tightly with internal and external partners on the technical strategy for user segmentation at scale, combining clickstream, CRM (customer relationship management), product telemetry, and campaign data to power personalized experiences.
• Architect and deliver production-grade personalization models for website and outbound channels (email, push, lifecycle, campaign orchestration).
• Lead complex ML (machine learning) efforts from problem framing to deployment, monitoring, drift detection, retraining strategy, and business readouts.
• Partner deeply with SME's (subject matter experts) and cross-functional teams to guide LLM (large language model) engineering direction, including model selection, evaluation frameworks, prompt/system design, grounding patterns, and responsible deployment practices.
• Establish robust evaluation and governance standards across classical ML and LLM systems (quality, safety, reliability, latency, and cost).
• Influence multi-team roadmap and investment decisions through opportunity sizing, forecast modeling, and clear executive communication.
• Mentor other individual contributors through technical leadership, design reviews, and reusable patterns that raise the bar across the organization.
• Sets technical direction for a significant problem space spanning multiple teams.
• Operates autonomously on ambiguous, high-impact initiatives with durable business outcomes.
• Creates methods, frameworks, and standards adopted beyond immediate project boundaries.
• Acts as a recognized technical leader in both advanced analytics/ML and emerging AI capabilities.

Required/minimum qualifications

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

Additional or preferred qualifications

• High proficiency in Python and SQL with command of large-scale data processing and feature engineering.
• Experience building segmentation and personalization systems using large behavioral datasets (including clickstream).
• Experience in experimentation, causal inference, and statistical decision frameworks.
• Experience leading cross-functional technical initiatives as an individual contributor.
• Demonstrated ability to translate complex analyses into executive-level recommendations.
• Experience with real-time or near-real-time personalization architectures.
• Deep familiarity with LLM engineering practices, including eval harnesses, RAG/grounding patterns, prompt workflows, and model operations.
• Experience with synthetic experimentation methods and simulation-based design.
• Knowledge of responsible AI, model risk management, and governance in enterprise environments.
• Track record of creating reusable platforms/assets that improve organizational velocity.

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.