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# Principal Research Data Scientist

- **Company:** HealthLeap Inc.
- **Location:** San Francisco, CA, United States
- **Experience:** Experienced
- **Salary:** $170,000.0 - $215,000.0
- **Contract:** Permanent contract
- **Skills:** Hospital Information Systems, Databases, Python (Programming Language), Electronic Medical Records
- **Published:** July 18, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=003214edf08b8391

## About the Role

* PhD in statistics, biostatistics, epidemiology, or a related field.
 * At least 2 years of (non-PhD) experience conducting observational health research using large healthcare databases.
 * Background in epidemiology or outcomes research.
 * Deep expertise in causal inference on observational data: difference-in-differences, regression discontinuity, interrupted time series, propensity methods.
 * Fluency in Python, including the ability to wrangle large, observational clinical datasets.
 * A track record of owning analyses or full research projects independently.

Bonus

 * Hands-on experience with EHR, claims, and billing data.
 * Familiarity with healthcare quality metrics and health system benchmarking.
 * Experience presenting research at conferences or to external audiences.
 * Exposure to claims or billing data.
 * Industry experience, though strong academic candidates are welcome.

## Description

At HealthLeap, you'll ask the hard questions about hospital care. Who gets missed, and for which conditions? What actually changes outcomes? Where does screening help, and where doesn't it? You'll run the statistical analyses that test whether screening every patient really changes their trajectory, look hard at the results, and figure out where we can do better. That work supports our partners and our go-to-market efforts, and it can shape a product that clinicians use every day.

You'll be early enough to build the research agenda from scratch, but late enough to know the product already works. You'll also have a lot to work with: EHR data from 40+ hospitals, hundreds of thousands of patients, real deployments, and your pick of health system partners. You'll get support from, and work closely with, our data science and engineering teams, who know the data inside and out.

You might be a good fit if you're curious, care about impact, and want to do applied data science. It helps if you like turning messy observational hospital data into results people actually cite, and if you're excited by the speed of startups!


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