Data Scientist, HealthLeap

• 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
• 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

Desirable

• 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
• 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

• 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