| Microsoft Careers

What you'll do

• Define and lead technical strategy for causal modeling and virtual experimentation to de-risk decisions.
• Architect production-grade personalization models using clickstream, CRM, product telemetry, and campaign data.
• Lead complex ML efforts from problem framing through deployment and monitoring.
• Partner with SMEs to guide LLM engineering direction including model selection and evaluation frameworks.
• Establish robust evaluation standards for classical ML and LLM systems across quality and safety metrics.
• Mentor other contributors through technical leadership and design reviews to raise organizational standards.
• Set technical direction for significant problem spaces spanning multiple teams.

What we're looking for

• Doctorate or equivalent experience in data science-related fields with substantial industry experience.
• High proficiency in Python and SQL for large-scale data processing and feature engineering.
• Experience building segmentation and personalization systems using behavioral datasets like clickstream.
• Expertise in experimentation, causal inference, and statistical decision-making frameworks.
• Ability to lead cross-functional technical initiatives and translate complex analyses into executive recommendations.
• Deep familiarity with LLM engineering practices including evaluation and responsible deployment.
• Experience with synthetic experimentation methods and real-time or near-real-time personalization architectures.