The Opportunity

Healthcare costs are rising, and employers and health plans need proof that digital MSK solutions deliver measurable savings. As a Health Economist at Hinge Health, you'll be the analytical engine behind our commercial success—designing and executing rigorous ROI studies that demonstrate how our platform transforms member outcomes while reducing costs for over 20 million lives. You'll translate complex claims data into compelling narratives that close deals, inform product strategy, and publish groundbreaking research that positions Hinge Health as the evidence-based leader in digital MSK care.

What You'll Accomplish

In your first 3 months, you will:

Build relationships with Client Success, Marketing, and Commercial teams to understand their analytical needs and prioritize high-impact ROI studies

Audit existing health economics methodologies and identify opportunities to streamline study designs while maintaining rigor

Complete your first client-facing cost analysis, presenting preliminary findings to internal stakeholders

In your first 6 months, you will:

Lead end-to-end execution of claims-based ROI studies, including vendor coordination for data acquisition, data transformation in SQL/Python, and analysis using advanced econometric methods

Partner with Client Success teams to present study results to external clients (health plan analysts, actuaries), translating technical findings into actionable insights

Contribute to clinical study design by identifying key health economics endpoints and measurement strategies

In your first year, you will:

Own the health economics research agenda for a specific MSK condition or product line (e.g., chronic back pain, women's pelvic health), acting as the go-to expert for commercial teams

Publish at least one peer-reviewed manuscript or conference presentation that elevates Hinge Health's thought leadership in digital health economics

Build reusable data pipelines from Hinge Health's claims and EHR warehouse (Databricks) that reduce study turnaround time by 30%

Who You Are

A Learn-it-all: You stay on the cutting edge of MSK and digital health research, constantly refining your methods and bringing new ideas to the team.

You don't just replicate studies—you improve them.

A Translator: You fluently speak both "data science" and "business," effortlessly moving between technical discussions with actuaries and strategic conversations with commercial leaders.

You know when to prioritize speed over perfection to meet commercial deadlines.

Accountable: You balance multiple competing priorities—ad hoc client requests, long-term research projects, and internal cross-functional needs—without dropping the ball.

You meet commitments and communicate proactively when timelines shift.

Hustler with Rigor: You find creative solutions to data limitations and study design challenges, always delivering defensible, high-quality results that can withstand external scrutiny.

Basic Requirements

Graduate degree (Master's or PhD) in health economics, health services research, epidemiology, or a related quantitative field

3-5 years of experience using applied econometric methods (e.g., casual inference, cost-effectiveness analysis, budget impact modeling) to address healthcare cost questions

3-5 years of hands-on experience working with large-scale commercial, Medicare, or Medicaid claims databases, including understanding of medical billing practices and health insurance structures

Fluent programming skills in R, SQL, and/or Python for data manipulation, statistical analysis, and visualization

Preferred Requirements

PhD in health economics or health services research

2-5 years of experience with Databricks, Snowflake, or similar cloud-based data platforms

Prior publication record in peer-reviewed journals (e.g., Health Affairs, Medical Care, JAMA) or experience presenting at academic/industry conferences

Experience in digital health or MSK care, including familiarity with value-based care models and population health analytics

Familiarity with AI tools (e.g., Claude, GitHub Copilot) for accelerating code development and data analysis