Director, Health Economics & Outcomes Research (HEOR)

Responsibilities

• Take the questions that growth, strategy, and clinical teams need answered and design, plan, and execute the health-outcomes analyses that answer them, using biometric, claims, and clinical data for both internal and external audiences.
• Apply modern AI tools (e.g., LLM-based assistants) in your day-to-day workflow to accelerate literature review, analysis, code, and manuscript drafting, with demonstrated proficiency, not just familiarity.
• Conduct literature reviews, run the analyses, and prepare manuscripts for peer-reviewed journals and clinical white papers, carrying work from concept to submission.
• Apply methods such as multilevel/mixed-effects modeling, survival analysis, case-control difference in difference, budget impact analysis, and clustering (e.g., K-means, DBSCAN) to complex, time-series, and nested data structures.
• Partner with growth, strategy, and clinical teams to generate the economic and clinical evidence that supports enterprise sales, client retention, and value-based care contracting.
• Work fluently with medical and pharmacy claims to quantify utilization, cost, and savings outcomes.
• Monitor pipelines for measurement fidelity and quality, and curate and prepare biometric, claims, and clinical data for analysis.
• Cook up evidence and reporting projects across product, marketing, engineering, and business development, providing the project-management structure that keeps multi-stakeholder work on track.

Qualifications

• Bachelor's degree required.
• 5-7+ years of hands-on experience in clinical analytics, HEOR, health economics, digital health, or a related domain.
• Demonstrated, hands-on experience analyzing healthcare claims data and applying rigorous statistical methods required.
• High proficiency in at least one statistical package: Python (preferred) or R; fluency in SQL.
• Startup/growth-stage experience; equivalent scrappy operating experience within a larger org also works.
• Comfortable sourcing your own data and delivering rigorous work without the infrastructure, resources, or processes of a large organization.
• Experience with time-series and nested/longitudinal data.
• A record of peer-reviewed publications or research projects, ideally in digital health, telemedicine, or value-based care.
• Proven ability to take a business question and independently carry it to a published result: scoping, analyzing, and delivering with minimal oversight.
• Demonstrated, hands-on proficiency using AI tools (e.g., LLM-based assistants) to do analytical and writing work more efficiently and to a higher standard.
• Ability to translate technical findings into clear, persuasive insight for non-technical executives, commercial, and external audiences.
• Familiarity with HIPAA and data-privacy requirements as they relate to PHI and digital health.