Jennifer Shyu

About Jennifer Shyu

I have extensive experience translating complex AI and data systems into scalable, high-impact products at Microsoft and eBay. My work has focused on building enterprise-scale platforms, AI-enabled workflows, and near real-time data systems grounded in master data management, entity resolution, LLM-driven analytics, and governed AI pipelines that deliver measurable business impact. I am now intentionally pivoting into Health Tech and health-adjacent AI, where data quality, explainability, identity resolution, and trust are foundational. I am actively expanding my healthcare domain expertise and seeking roles where I can apply enterprise-grade AI platforms and recommender system experience to improve patient engagement, operational efficiency, and population health outcomes.At Microsoft, I led product strategy for enterprise data and AI platforms supporting the Cloud + Enterprise ecosystem. This included LLM-based company name and address matching using third-party data, enterprise identity resolution, customer hierarchy modeling, and real-time platform modernization. My work strengthened platform trust, improved data precision, and unlocked downstream revenue and analytics use cases across the enterprise. At eBay, I spent over a decade in product leadership roles, including four years leading AI-driven email recommendation systems. I partnered closely with data science teams to deliver personalized, model-driven customer experiences at global scale, driving engagement through experimentation, real-time pipelines, and applied machine learning.

Experience

1. Senior Product Manager C E, Signup Experience

   Microsoft

   Jan 2024 — Present

   Led product strategy for Microsoft’s Organization Repository (MOR), unifying customer identities across 12+ systems and enabling scalable AI segmentation, real-time data ops, and $100M+ in revenue impact.• Directed a $60M vendor transition from D&B to Moody’s, improving data coverage, reducing licensing costs, and aligning external sourcing with long-term AI strategy.• Enhanced LLM-based matching logic, boosting precision by 35% in firmographic hierarchy modeling and resolving fragmented org identities across global enterprise accounts.• Contributed to modernization of Microsoft’s signup experience, embedding telemetry and governance into onboarding flows and laying the foundation for adaptive UX and scalable personalization across Cloud + Enterprise platforms.

Education

• Arizona State University

  Bachelor, Finance

• University of California, Berkeley, Haas School of Business

  Executive Education, Product Management

  2018

• Illinois Institute of Technology

  Master of Business Administration - MBA, MIS