HealthLeap
Principal Research Data Scientist
San Francisco Office · Principal
Sponsorship not specified$170k-$215kDetected 6 days ago
PythonData ScienceStatisticsCustomer SuccessEHR/EMRResearchExperimental DesignPublic SpeakingBiostatisticsEpidemiology
About the role
- At HealthLeap, you'll ask the hard questions about hospital care.
- Who gets missed, and for which conditions?
- Where does screening help, and where doesn't it?
Responsibilities
- Own research projects end-to-end, from study design through analysis, interpretation, and publication.
- Design and run observational and quasi-experimental studies on real-world hospital data.
- You'll be early enough to build the research agenda from scratch, but late enough to know the product already works.
- You'll get support from, and work closely with, our data science and engineering teams, who know the data inside and out.
- You'll be our first dedicated research hire, which means you get to help set research priorities for HealthLeap and own your research portfolio.
Requirements
- 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.
- Hands-on experience with EHR, claims, and billing data.
- Experience presenting research at conferences or to external audiences.
Compensation
- $170,000 to $215,000.
Benefits
- HealthLeap is building the AI operating system that helps care teams identify these missed patients, enabling them to improve health outcomes and generate millions of dollars.
- Over the past year, we've grown contracted revenue more than 13x, expanded rapidly across leading health systems, and now help care teams identify patients across millions of inpatient encounters.
- EHR data from 40+ hospitals, hundreds of thousands of patients, real deployments, and your pick of health system partners.
- At least 2 years of (non-PhD) experience conducting observational health research using large healthcare databases.
- Familiarity with healthcare quality metrics and health system benchmarking.
- If you're passionate about applying frontier AI to real-world impact, join us in building healthcare's future.
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This listing is sourced directly from HealthLeap's careers page and normalized into a canonical job model.