Data scientist [h1.location_city]

About Healthleap

HealthLeap builds AI that helps clinicians prioritize patients, surfaces the right data, and gets patients the care they need earlier, so they can leave the hospital sooner.

We integrate with hospital electronic health record systems, screen 100% of patients daily, and risk-rank them in real time. Clinicians at Cedars-Sinai and Penn Medicine start every morning with HealthLeap — with Houston Methodist, Emory, and Intermountain Health deploying now.

Real results : 39% more diagnoses. 4 days earlier detection. $11M / year ROI for our first site at Cedars Sinai. 7× revenue growth in 7 months.

We started with malnutrition. We're expanding to every major condition to ensure no patient falls through the cracks. Sequoia and First Round are backing us to build the platform that screens every patient for everything and drives tangible outcomes.

We're ~15 people. >

$7M raised. SF-based, hybrid-friendly. Early enough to shape the product. Late enough to know it works. Results that are changing lives.

About the Role

Prove that our models save lives. Then ship more of them.

You'll own the full loop : problem framing, experimental design, model iteration, retrospective validation, and customer-ready deployment. Weeks, not months. You'll work directly with our CEO to launch new conditions, run pilots that prove clinical and financial impact, and present your work to AI / Data Science leaders at world-class health systems.

Why you

You have a sound theoretical foundation but care more about outcomes than papers. You've shipped models that actually changed something. You're comfortable in front of customers defending your methods. You move fast, iterate faster, and know when good enough beats perfect.

What you'll do

Expand to new conditions : idea → signal viability → validated model → customer-ready. Weeks, not months.

Prove impact with rigorous retrospective analyses : LOS reduction, readmission reduction, mortality reduction. Clear confidence intervals. Robust counterfactuals.

Transition validated pilots into live deployments that deliver measurable outcomes

Own end-to-end modeling : from financial incentives and problem framing to a deployed model

Productionize pipelines with reliability

Monitor and improve : drift detection, calibration, uncertainty, fairness

Partner with stakeholders : clear visuals, crisp narratives, method presentations for analysts, clinicians, and executives

Meet with AI / Data Science leaders at health systems to share your model assumptions and methodologies

What we're looking for

3-5+ years relevant experience in a high-growth environment

BS / MS in Statistics, Biostats, CS, or equivalent experience

Statistics depth : parametric and non-parametric tests, hypothesis testing, experimental design, confidence intervals, causal inference basics

ML fluency : Python, SQL, polars / pandas, scikit-learn, XGBoost / LightGBM

Visualization & storytelling : Turn complex analyses into crisp dashboards and narratives for clinicians and executives

Customer-facing : Comfortable interviewing stakeholders, presenting to technical leaders, defending your methods

Passionate about AI's potential in healthcare. Outcomes-oriented.

Resourceful, high ownership, bias to action, fast experimentation cycles

Nice to have

Background at an applied AI company with real product traction (not hype-driven firms)

Healthcare data experience (EHR schemas, FHIR / HL7, IRB / validation study workflows)

Survival / time-to-event modeling

Uncertainty quantification

Covariate and prediction drift detection in production

LLMs for clinical text, weak / active / semi-supervised learning

PyTorch / transformers experience

Side projects that show you can productionize, not just prototype

This role is NOT for you if

Startup unpredictability feels like chaos to you. We find it exciting.

You need detailed specs before you start. We figure it out as we go.

You've never owned something end-to-end. Here, you own outcomes, not tasks.

You wait to be told what to do next. We need people who see what's needed and do it.

You're looking for a 9-5 with predictable hours. We care about deep work and deep rest (we have a minimum leave policy), but when a hospital go-live is on the line, we show up - even if that means a 60+ hour week.

Interview process

Intro call - Get to know each other

Technical - 1-2 interviews on statistical methodology + past work deep dive

Onsite - Case study, presentation, team meet

Decision - Same week as onsite

We respect your time. If there's a fit, you'll know fast.

Compensation & Benefits

Salary : $190,000 - $280,000 base

Equity : Meaningful ownership in an early-stage company

Healthcare : 100% of premiums covered

PTO : Unlimited, with a recommended minimum of 20 days

401(k) : 4% match

Equipment : Laptop + budget for your home office

In-office : Lunch, snacks, and drinks provided

Location

San Francisco, hybrid (Mon / Wed / Fri in office)

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

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