Global RWE Leader – Oncology Strategy

Biopharma Careers; Raritan, Northern (NJ, KY); Hybrid; USD 140,000 - 190,000; Full time

Job summary

Johnson & Johnson is seeking an Associate Director, Global Real-World Evidence, Oncology, to support development and execution of RWE strategies in the oncology portfolio. Based in Raritan, NJ, this role partners with cross-functional teams to translate evidence into actionable insights for market access and medical affairs.

The ideal candidate has a PhD preferred in epidemiology or related field, 5+ years in RWE, and strong programming skills (SAS, R, Python) with global study experience.

Qualifications

• Advanced degree required in epidemiology, pharmacoepidemiology, health economics and outcomes research, public health, biostatistics, health policy, or related field.
• PhD preferred.
• Minimum 5 years of relevant experience in pharma/biotech/consulting/healthcare.
• Experience with real-world evidence studies, analytics, and dissemination.
• SAS, R, Python knowledge preferred.
• Oncology experience strongly preferred.

Responsibilities

• Support the design and execution of global RWE studies and evidence-generation projects across oncology.
• Collaborate with researchers, programmers, and vendors to translate study concepts into protocols and analyses.
• Provide methodological input on observational study designs and bias mitigation.
• Support governance, prioritization, and project execution in a global matrix environment.

Skills

Project management

Scientific writing

Data interpretation

Cross-functional collaboration

Communication skills

Education

PhD in epidemiology/HEOR/public health/biostatistics

Tools

SAS

R

Python

Job description

Johnson & Johnson is seeking an Associate Director, Global Real-World Evidence, Oncology, to support development and execution of RWE strategies in the oncology portfolio. Based in Raritan, NJ, this role partners with cross-functional teams to translate evidence into actionable insights for market access and medical affairs.

The ideal candidate has a PhD preferred in epidemiology or related field, 5+ years in RWE, and strong programming skills (SAS, R, Python) with global study experience.