Responsibilities
- Manage a Hybrid Inference Roadmap: Develop and execute strategy for core prediction models serving direct productization and tech-enabled service use cases.
- Navigate Internal Complexity: Bring clarity and alignment among Engineering, Science, Go-to-Market, and Product teams.
- Drive External Partnerships: Act as primary interface for partners, translating scientific requirements into model capabilities and managing expectations.
- Bridge the Gap (Science <> ML): Translate preclinical business objectives into technical and data requirements to serve multiple drug discovery use cases.
- Measure Impact: Define and report metrics capturing platform value beyond model performance, demonstrating ROI and scientific utility.
Requirements
- 5+ years, preferably 7+ years, as a Product Manager with increasing responsibility in AI/ML or Data Science products.
- Biopharma/Preclinical Fluency: Understanding of drug discovery lifecycle and scientific workflows.
- Experience with Probabilistic Products handling uncertainty and confidence in high-stakes environments.
- Experience in Technology-as-a-Service managing inference technology consumed via API or service layer.
- Exceptional Stakeholder Management with ability to navigate internal politics and drive consensus.
- Technical Fluency: Familiarity with LLMs, Knowledge Graphs, or predictive modeling and understanding of trade-offs.
- Strategic Resilience: Comfortable with ambiguity and making data-informed decisions amidst uncertainty.
Benefits and Perks
- Equity options and competitive compensation package.
- Robust vacation policy, additional vacation days, and company closures for 14 days annually.
- Flex time for sick days, personal days, and religious holidays.
- Comprehensive health and dental benefits.
- Annual learning & development budget and home office set-up budget.
- Lifestyle spending account allowance.
- Generous parental leave benefits with top-up plans or paid time off.
- Retirement savings with company match.
