Senior Product Manager - QuantHealth

Experience: 5+ years of Product Management, specifically on complex, data-heavy, or B2B SaaS platforms. Execution Track Record: Proven ability to own a product end-to-end - backlog to launch - in a fast-paced environment with high autonomy. Analytical Mindset: Comfortable with data, metrics, and quantitative concepts. A background in statistics, biostatistics, data science, or engineering is a strong plus. Prior exposure to healthcare, clinical trials, or life sciences is also valued. Builder Instinct: Experience working hands-on with data or prototyping tools (Python, SQL, or AI coding environments) is preferred but not required. Communication: Able to work across highly technical teams and translate complexity into clear decisions and crisp product specs.

Product Ownership: Own the end-to-end product lifecycle for our core Clinical Trial Simulator backlog, sprint planning, prioritization, and delivery in close partnership with engineering. Stakeholder Translation: Partner with pharma users and internal domain experts to turn complex clinical workflows into clear, well-scoped product requirements. Cross-Functional Execution: Serve as the connective tissue between data science, engineering, and commercial teams and keep delivery moving without losing sight of user impact. User Discovery: Run continuous discovery with pharma stakeholders to surface high-value problems, validate assumptions, and pressure-test solutions against real clinical workflows. Data-Informed Decisions: Use product analytics, user feedback, and clinical data context to prioritize what gets built and measure whether it's working. AI Tooling: Leverage AI development tools where useful to prototype, explore, and accelerate early-stage product thinking.

Experience: 5+ years of Product Management, specifically on complex, data-heavy, or B2B SaaS platforms. Execution Track Record: Proven ability to own a product end-to-end - backlog to launch - in a fast-paced environment with high autonomy. Analytical Mindset: Comfortable with data, metrics, and quantitative concepts. A background in statistics, biostatistics, data science, or engineering is a strong plus. Prior exposure to healthcare, clinical trials, or life sciences is also valued. Builder Instinct: Experience working hands-on with data or prototyping tools (Python, SQL, or AI coding environments) is preferred but not required. Communication: Able to work across highly technical teams and translate complexity into clear decisions and crisp product specs.