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
Originally posted on Himalayas
