Associate Director, RWE Statistics

Role Summary

The Associate Director, Real-World Evidence (RWE) Statistics sits within Global Statistics & Data Science (GSD) and partners with cross-functional teams in Teva R&D to provide statistical strategy and technical leadership for analysis of Real-World Data (RWD) and other data sources to support lifecycle drug development. Responsibilities include statistical input to evidence generation planning, medical affairs and RWE research proposal reviews, study protocol and SAP development and execution, results interpretation, scientific presentations and publications, interactions with agencies, and RWE/statistical methodology research. The role aims to elevate data generation, inform decision-making, and improve patient outcomes. The preferred candidate will be based in West Chester, PA, or Parsippany, NJ, or remote for the right candidate.

Responsibilities

• Lead RWE statistical input for evidence generation planning for assigned TAs/assets, collaborating with global and regional Medical Affairs, Health Economics, Value and Outcomes, and other R&D stakeholders.
• Develop and review study concepts and protocols, ensuring alignment with objectives and appropriate sample size and statistical methods for scientific, regulatory, and market access needs.
• Lead or oversee SAP development and execution, including table, figure, and listing shells, and output review; collaborate with programmers/analysts to ensure timely, high-quality statistical deliverables; develop data review plans and interpret complex data.
• Provide in-depth statistical review for scientific publications and reports; ensure appropriate statistical analysis and results are consistently applied in all scientific and regulatory documents, presentations, and publications.
• Contribute to external interactions with regulators, payers, and other agencies.
• Demonstrate advanced statistical concepts; lead the introduction of innovative statistical methods (e.g., causal inference, bias and confounding control, AI/ML) into analysis plans; explain statistical concepts to non-statisticians.

Qualifications

• PhD (4+ years of experience) or MS (6+ years) in Biostatistics, Statistics, or related quantitative field.
• Pharmaceutical or related industry experience required.
• Competence in RWE study design, statistical modeling, and AI/ML methods for observational data; knowledge of confounding control and bias minimization highly desired.
• Expertise with multiple RWD sources (e.g., EHR, claims, registry data); familiarity with clinical trial design.
• Proficiency in SAS, R, and/or Python; cloud-based analytics platforms a plus.
• Ability to build strong cross-functional relationships; drive data-driven innovation and high performance.
• Motivated to learn new methodologies; open-minded and adaptable; enthusiastic about innovation and impact.
• Excellent writing and communication skills; demonstrated leadership and project management abilities.
• Experience supporting HTA submissions or regulatory interactions preferred.
• Track record of publications or presentations in RWE methods preferred.
• Familiarity with ADaM/SDTM data standards and data privacy regulations preferred.

Skills

• Statistical leadership in RWE and real-world data analysis
• Study design, SAP development, and data interpretation
• Regulatory and payer interactions
• Advanced statistical methods (causal inference, AI/ML)
• Cross-functional collaboration and communication

Education

• PhD in Biostatistics or Statistics or MS with substantial relevant industry experience (as specified above)

Additional Requirements

• Location flexibility: West Chester, PA; Parsippany, NJ; or remote for right candidate