Director- RWD Scientist

Eli Lilly and Company; United States; Presencial; USD 140 000 - 210 000; Tempo integral

Resumo da oferta

Lilly is seeking a Lead for real-world data (RWD) efforts within the Cardiometabolic Health (CMH) portfolio. The role focuses on evidence generation to support product development, regulatory, and market access strategies.

Responsibilities include designing complex RWD studies using claims and health records data, translating ideas into insights, and collaborating with global teams. Remote work with Indianapolis-based preference and travel may be required.

Qualificações

• PhD or MD with 5+ years in outcomes research, epidemiology, health economics, or data science.
• Hands-on RWD analysis using statistical software (R, SAS, Python).
• Expertise in health technology assessment, real-world evidence, and epidemiology.

Responsabilidades

• Design and execute complex RWD studies using claims and health records data; translate ideas into actionable insights.
• Drive strategic planning for patient-focused outcomes, health economics, and outcomes research; communicate findings to stakeholders.

Conhecimentos

Outcomes research

RWD analysis

Epidemiology

Health economics

Data science

Formação académica

PhD or MD

Ferramentas

R

SAS

Python

Descrição da oferta de emprego

Role: Lead scientific efforts in real-world data (RWD) for Lilly's Cardiometabolic Health (CMH) portfolio, focusing on evidence generation to inform product development, regulatory, and market access strategies.

Responsibilities

• design and execute complex RWD studies using claims and health records data, translate scientific ideas into actionable insights, and integrate emerging technologies like AI and privacy-preserving data solutions.
• Drive strategic planning for patient-focused outcomes, health economics, and outcomes research; influence cross-functional teams; and communicate findings to internal and external stakeholders.

Requirements

• PhD or MD with 5+ years of experience in outcomes research, epidemiology, health economics, or data science, including hands‑on RWD analysis skills utilizing statistical software (e.g., R, SAS, Python).
• High-value specifics: expertise in health technology assessment, real-world evidence, and epidemiology; familiarity with US, European, or Asian healthcare systems; experience with healthcare delivery models; and ability to collaborate globally.

Work setup

• primarily remote, based in Indianapolis preferred;
• domestic and international travel may be required.