The Staff Data Scientist on the Clinical Performance team will lead the design and implementation of advanced causal inference and statistical frameworks to measure and forecast the effectiveness of Pearl's clinical products and operational services.
Requirements
Graduate degree in a quantitative field such as Statistics, Economics, Biostatistics, or Epidemiology
8+ years of experience in results-driven quantitative analysis
Experience implementing causal inference methodologies in real-world, messy data environments
Expert-level proficiency in Python and SQL
Experience building scalable data science systems and infrastructure within a modern cloud environment (AWS, Snowflake, dbt) Benefits
Competitive benefits package
Discretionary performance bonus
Equity options
