Staff Data Scientist, Clinical Performance

THE OPPORTUNITY

As a Staff Data Scientist on the Clinical Performance team, you will be the lead architect of the methodologies that prove Pearl Health’s impact on the American healthcare system. You will tackle the massive challenge of untangling overlapping clinical interventions to isolate exactly what drives better patient outcomes and financial sustainability. Reporting to the Senior Director of Clinical Performance, you will play a defining role in building the feedback system that guides our company strategy and validates our mission to empower primary care providers.

While your primary focus is evaluative, you will be a key player in the broader clinical DS ecosystem, collaborating on patient risk stratification and building the forecasting engines that predict our quality performance across various value-based care programs.

WHAT YOU'LL DO

You will lead the design and implementation of advanced causal inference and statistical frameworks to measure and forecast the effectiveness of Pearl’s clinical products and operational services.

- Architect Causal Frameworks: Design and build the scalable systems required to conduct rigorous impact analyses, moving beyond simple correlations to isolate the true "Pearl Effect" on patient populations. Set the technical bar for how we handle complex data challenges, including non-randomized treatment assignment, selection bias, and compounding intervention effects.

- Forecast Quality & Performance: Develop predictive models to issue forecasts for clinical quality measures (including eCQMs in MSSP and claims-based measures in REACH and LEAD). This includes establishing the "status quo" baseline to accurately quantify Pearl's incremental impact.

- Collaborate on Patient Risk: Partner with other Staff Data Scientists to refine and validate patient risk models, ensuring that "rising acuity" signals are integrated effectively into our performance evaluation loops.

- Lead Technical Execution: Partner with Engineerin...