Data Scientist II, Real World Evidence (RWE), Pharma R&D
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The role
Lead observational Real World Evidence studies in oncology using real-world clinical data to address trial design and outcomes research.
Derive complex endpoints, apply time-to-event/survival analyses, and implement causal inference methods.
Leverage AI tools and LLM-based workflows to accelerate coding, documentation, discovery, and insight generation.
Collaborate with pharma partners and cross-functional teams to translate data findings into actionable insights for decision-makers.
Ensure rigorous methodology, maintain reusable code and internal packages, and uphold software engineering practices.
Communicate results clearly to technical and non-technical stakeholders; preferred experience in oncology, genomics, and clinical trials.
Derive complex endpoints, apply time-to-event/survival analyses, and implement causal inference methods.
Leverage AI tools and LLM-based workflows to accelerate coding, documentation, discovery, and insight generation.
Collaborate with pharma partners and cross-functional teams to translate data findings into actionable insights for decision-makers.
Ensure rigorous methodology, maintain reusable code and internal packages, and uphold software engineering practices.
Communicate results clearly to technical and non-technical stakeholders; preferred experience in oncology, genomics, and clinical trials.
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