Principal Research Data Scientist

HealthLeap

Principal Research Data Scientist at HealthLeap applying AI for patient care prioritization. Engaging in observational studies and leading research to improve healthcare outcomes.

Posted 7/16/2026full-timeSan Francisco • California • 🇺🇸 United StatesLead💰 $170,000 - $215,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and conducting observational health research, with a strong focus on causal inference methods and the ability to analyze complex clinical datasets using Python. Proven track record of leading research projects from inception to publication while collaborating effectively with diverse teams.

Highest-signal resume keywords

PhD In StatisticsEpidemiology ExpertiseCausal Inference MethodsPython ProficiencyObservational Health Research

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Study DesignData AnalysisStatistical MethodsRegression DiscontinuityInterrupted Time SeriesPropensity MethodsData InterpretationResearch Project ManagementQuantitative ResearchHealth Outcomes Research

Soft Skills

CollaborationCommunicationProblem-SolvingLeadership

Industry Keywords

Healthcare DatabasesObservational StudiesQuasi-Experimental StudiesClinical DatasetsHealth System Partnerships

Tech Stack

Tools & technologies

Python

About the role

Key responsibilities & impact

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.
Analyze complex clinical and operational datasets and stand behind the methods.
Collaborate with frontline clinicians, health system execs, our customer success team, our go-to-market teams, and our data science team to come up with new research questions, weigh in on product decisions, and lead the outcomes and impact studies tied to our health system partnerships.

Requirements

What you’ll need

PhD in statistics, biostatistics, epidemiology, or a related field.
At least 2 years of (non-PhD) experience conducting observational health research using large healthcare databases.
Background in epidemiology or outcomes research.
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.

Benefits

Comp & perks

Salary: $170,000 to $215,000.
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 plus a home office budget.