- Set the strategy for search, retrieval, and ranking, aligning stakeholders across engineering, data science, design, clinical, and executive teams.
- Run the full lifecycle of the experimentation program, including objective functions, guardrail metrics, and honest performance readouts.
- Build the data, evaluation, and ML platform foundations required for long-term matching scalability.
- Collaborate daily with ML engineers and data scientists on model objectives, feature development, and evaluation.
- Represent ranking priorities across the organization, managing trade-offs between patient experience, provider growth, clinical quality, and payer partnerships.
- Set the professional standard for technically grounded product management across the broader PM team.
Machine LearningProduct ManagementData science