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. The role includes 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 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 tables, figures, and listing shells; review outputs and collaborate with programmers/analysts to ensure timely, high-quality deliverables; develop data review plans and interpret complex data.
• Provide in-depth statistical review for scientific publications and reports; ensure appropriate analysis and results are consistently applied in documents, presentations, and publications.
• Contribute to external interactions with regulators, payers, and other agencies.
• Demonstrate advanced statistical concepts and lead the introduction of innovative methods (e.g., causal inference, bias and confounding control, AI/ML) into analysis plans; explain statistical concepts to non-statisticians.

Qualifications

• PhD (with 4+ years of experience) or MS (with 6+ years of experience) 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 desirable.
• Experience 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 are a plus.
• Ability to build strong cross-functional relationships; data-driven mindset; high performance.
• Strong writing and communication skills; 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 clinical trial data standards (ADaM/SDTM) and data privacy regulations preferred.

Skills

• Statistical analysis, study design, SAP development, data interpretation
• RWE, observational data methodologies, confounding control
• SAS, R, Python, cloud analytics
• Stakeholder collaboration, scientific communication, regulatory interactions

Education

• PhD in Biostatistics/Statistics or related field with 4+ years of experience, or MS with 6+ years of experience