Staff Data Scientist, Clinical Performance
Source: Himalayas
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This role involves leading the design and implementation of advanced causal inference and statistical frameworks to measure and forecast the effectiveness of clinical products and services. The ideal candidate has 8+ years of experience in quantitative analysis, expert Python and SQL skills, and experience with cloud data infrastructure.
Job Description
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.RequirementsGraduate degree in a quantitative field such as Statistics, Economics, Biostatistics, or Epidemiology8+ years of experience in results-driven quantitative analysisExperience implementing causal inference methodologies in real-world, messy data environmentsExpert-level proficiency in Python and SQLExperience building scalable data science systems and infrastructure within a modern cloud environment (AWS, Snowflake, dbt)BenefitsCompetitive benefits packageDiscretionary performance bonusEquity optionsOriginally posted on Himalayas
Full Description
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.RequirementsGraduate degree in a quantitative field such as Statistics, Economics, Biostatistics, or Epidemiology8+ years of experience in results-driven quantitative analysisExperience implementing causal inference methodologies in real-world, messy data environmentsExpert-level proficiency in Python and SQLExperience building scalable data science systems and infrastructure within a modern cloud environment (AWS, Snowflake, dbt)BenefitsCompetitive benefits packageDiscretionary performance bonusEquity optionsOriginally posted on Himalayas