Senior Data Scientist - Real World Data

Role: Senior Data Scientist within the Scientific Data Intelligence team, focusing on transforming and analyzing Real World Data (RWD) such as EHR and claims to support drug development and scientific decision-making. Responsibilities: develop scalable data pipelines using SQL, Python, Dagster, dbt, and Snowflake; model and clean healthcare data adhering to standards like OMOP; conduct observational RWD studies on disease epidemiology, treatment patterns, and patient journeys; implement data validation and observability; apply Generative AI techniques to enhance data structuring and insights; communicate findings to technical and non-technical stakeholders. Requirements: 5+ years in data science or data engineering, with at least 2 years' experience in healthcare or life sciences, including hands-on work with EHR or claims data; proficiency in SQL, Python, and modern data tools; knowledge of biomedical schemas (UMLS, LOINC, ICD), RWD study design, and causal inference frameworks; experience constructing longitudinal cohorts and executing observational studies; familiarity with regulated data environments and commercial RWD vendors preferred. HighValue: healthcare data science, RWD transformation, Generative AI, disease epidemiology, causal inference, longitudinal cohort construction, regulated data handling. WorkSetup: hybrid model in NYC, Boston, Research Triangle, or Bay Area, requiring 3 days onsite; some relocation or residence in these locations necessary.