Scientific Director, Pharmaceutical Development Analytics

About the Role

The Scientific Director, CMC Quantitative Sciences is a senior technical individual contributor who designs and advances data‑driven development and lifecycle management initiatives for drug products. The director serves as the portfolio‑level statistical authority for drug product development programs from post‑Proof of Concept through regulatory submission and the commercial lifecycle. The role collaborates cross‑functionally with Pharmaceutical & Analytical Development, Quality, Regulatory CMC, and Commercial Manufacturing & Supply Chain to ensure that development and manufacturing decisions are supported by rigorous statistical analysis and defensible interpretation of CMC data.

• Pharmaceutical Development (CMC)
  • Owns drug product design and development strategy
  • Generates, maintains and leverages process understanding and development data
  • Informs control strategy for regulatory submission and hand‑off to commercial
  • Owns routine manufacturing execution and maintains continuity of supply to the market
  • Owns site‑level monitoring and operational performance (CPI/CPV strategy, design, oversight, monitoring and reporting)
• Scientific Director, Pharmaceutical Development Quantitative Sciences (This Role)
  • Provides advanced statistical analysis and modeling expertise across CMC programs
  • Translates complex development and manufacturing data into actionable technical insights
  • Ensures statistical rigor and regulatory defensibility of CMC data packages
  • Supports formulation and process development strategies through data‑driven insights and mechanistic interpretation
  • Supports troubleshooting efforts and root‑cause investigations on both the formulation and process development fronts for development and commercial assets
  • Applies multivariate tools to identify CMAs, CPPs, and design space boundaries
  • Provides statistical guidance for investigations involving process variability and rootcause analysis of complex development or manufacturing trends
  • Integrates datasets across development, analytical, and manufacturing functions to generate actionable insight
  • Translates experimental data into formulation and process understanding, including identification of critical material attributes, excipient functionality, and process sensitivities
  • Supports development teams in interpreting DoE outcomes to refine formulations and unit operations (granulation, blending, compression, coating)
• Formulation & Process Development Support
  • Partners with Pharmaceutical Development scientists to design and optimize formulations using structured experimental approaches (DoE, mixture designs, response surface methods)
  • Provides quantitative and mechanistic input into selection of excipients, formulation composition, and process parameters
  • Supports development and scale‑up of key unit operations (fluid bed granulation, roller compaction, blending, tableting, coating) through data‑driven modeling and risk assessment
  • Guides process characterization strategies (definition of parameter ranges, interaction effects, and scale dependencies)
  • Contributes to development of robust manufacturing processes by linking material attributes, process parameters, and product performance
  • Supports assessment of formulation and process robustness, including sensitivity analyses and failure mode identification
• Regulatory Submission Support
  • Primary statistical authority supporting CMC regulatory submissions (NDA, BLA, MAA)
  • Ensures statistical methodologies used in development and validation are regulatory defensible and aligned with ICH guidelines (Q8, Q9, Q10, Q14)
  • Provides statistical interpretation for process validation strategies and control strategy justification
  • Supports responses to regulatory questions related to CMC data analysis and statistical methodology
  • Contributes to justification of formulation composition, process design, and design space within regulatory filings
• Capability Building
  • Strengthens quantitative capabilities across Pharmaceutical Development
  • Drives adoption of modern data science and modeling approaches that improve development efficiency and process understanding
  • Establishes best practices for experimental design and statistical…