Founding Data Scientist

HealthLeap is an AI start-up revolutionizing healthcare through predictive analytics, initially focused on disease-related malnutrition-a critical form of patient deterioration affecting virtually every hospital condition. Our mission is to maximize health outcomes globally by building a scalable AI platform that screens patients comprehensively using electronic health records (EHRs), labs, clinical notes, and more.

We're experiencing explosive growth, with contracts and pilots at top US health systems like Cedars-Sinai, Intermountain Health, Penn Medicine, and many others. We have unprecedented access to EHR data (far more than competitors : 10s of billions of tokens per hospital + vast structured data across 100% of inpatients), positioning us to expand into additional conditions like pressure ulcers, congestive heart failure, infections, readmissions, and mortality predictions. With a unique strategy and no direct competitors (due to our 2+ year lead and regulatory advantages), we are setting out to become a $100B+ company.

Outcomes You'll Drive

Condition expansion velocity : Idea → signal & label viability using current EHR data → validated model → customer-ready (for viable use cases, weeks, not months)

Improving patient health outcomes : Quantified length of stay (LOS) reduction, readmission reduction, mortality reduction, with clear confidence intervals and robust counterfactuals.

Pilot → production conversion : Run retrospective analyses on hospital data to prove impact, then transition validated pilots into live deployments that deliver measurable outcomes.

Role Overview

We're looking to hire a product-minded Data Scientist with a sound theoretical knowledge foundation. You will own end-to-end problem framing, timeline scoping, experimental design, and model iteration. You'll work closely with our CEO and small team to launch new models quickly and safely by leveraging and expanding on our existing feature tables. You will also run retrospective pilots to estimate clinical and financial impact (reimbursement lift, LOS reduction, mortality reduction) and support pre-sales by meeting AI / Data Science leaders at world-class health systems to share your clinical and financial model assumptions and development methodologies.

Key Responsibilities

• Own end-to-end modeling from financial incentives and problem framing to a validated model.
• Estimate impact with rigorous retrospective analyses (LOS, readmissions, mortality, reimbursement).
• Productionize pipelines and rollouts with reliability.
• Monitor & improve : drift, calibration / uncertainty, and fairness (Independence / Separation / Sufficiency).
• Translate research into pragmatic wins for our platform.
• Partner with stakeholders : clear visuals, crisp narratives, and method presentation for analysts, clinicians, and executives.

Requirements

Nice-to-Haves

We Provide :

Location : San Francisco (hybrid)

Compensation is dependent on experience, overall fit to our role, and candidate location.

If you're passionate about applying frontier AI to real-world impact, join us in building healthcare's future.