RWE Stats & Data Science Lead

Tevapharm; West Chester (Chester County); On-site; USD 134,000 - 167,000; Full time

Benefits offered by this job

Health Insurance

401(k) with employer match

Paid Time Off

Life and Disability Insurance

Job summary

Teva is seeking a Senior Manager, Real‑World Evidence (RWE) Statistics & Data Science to lead statistical design and analysis for observational research using real‑world data. You will partner with cross‑functional teams to plan evidence generation and translate complex data into actionable insights for regulatory, medical, market access, and business decisions.

The role requires a PhD (2+ years) or MS (4+ years) in Biostatistics or a related field, with proficiency in R, SAS, and Python, and

Qualifications

• PhD or MS in Biostatistics or a related quantitative field.
• Proficiency in R, SAS, and/or Python.
• Experience working with large real‑world data (RWD) databases (claims, EHR, registries, surveys).
• Experience with observational study design and bias/confounding control.

Responsibilities

• Serve as the RWE Statistics lead for assigned programs and participate in internal meetings supporting evidence generation planning and development.
• Provide statistical input into the design and execution of observational studies, develop SAPs, protocols, and specifications.
• Partner with program teams to evaluate RWD sources and generate insights to inform decision‑making.
• Lead the statistical design, oversee execution, review and interpret results of internal RWD analyses.
• Apply advanced statistical methodologies and AI/ML‑based approaches.
• Clearly communicate statistical concepts and results to technical and non‑technical audiences.
• Contribute to capability development and AI adoption initiatives.

Skills

R

SAS

Python

Observational studies

Education

PhD in Biostatistics

MS in Biostatistics

Tools

RWD databases

Job description

Teva is seeking a Senior Manager, Real‑World Evidence (RWE) Statistics & Data Science to lead statistical design and analysis for observational research using real‑world data. You will partner with cross‑functional teams to plan evidence generation and translate complex data into actionable insights for regulatory, medical, market access, and business decisions.

The role requires a PhD (2+ years) or MS (4+ years) in Biostatistics or a related field, with proficiency in R, SAS, and Python, and