Principal Research Data Scientist

Responsibilities

• 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 executives, customer success, go-to-market, and data science teams to develop new research questions, weigh in on product decisions, and lead outcomes and impact studies tied to health system partnerships.

Requirements

• 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.

Core Competencies

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.