CMC Statistics Director

Job Description GENERAL

SUMMARY:

The CMC Statistics Director (Scientific Fellow) provides strategic and technical leadership for the application of statistical sciences across the product lifecycle, including process development, analytical development, manufacturing, process validation, continued process verification (CPV), stability, quality control, and regulatory submissions. This individual will establish and lead the CMC Statistics capability, enabling data-driven decision-making to enhance product quality, process robustness, operational efficiency, and regulatory compliance.

The role partners closely with Development, MSAT, Quality, Regulatory Affairs, and Data & Digital teams to ensure the effective application of advanced statistical methodologies across all CMC functions. The position will drive the adoption of best practices in statistical analysis, DOE, process monitoring, and manufacturing data analytics to support Vertex's growing portfolio and evolving manufacturing network. This individual will demonstrate Vertex Core Values while fostering a culture of scientific excellence, continuous improvement, innovation, collaboration, and quality.

• Partner with Development, Manufacturing, Quality, Regulatory Affairs, and Data & Digital organizations to provide strategic statistical leadership across the CMC lifecycle
• Establish and lead the CMC Statistics Center of Excellence, defining standards, governance, methodologies, and best practices for statistical analyses
• Provide statistical leadership for process characterization, process optimization, process robustness studies, technology transfer activities, and lifecycle management programs
• Support the application of Design of Experiments (DOE) methodologies to support product and process development, optimization, and control strategy development
• Develop and implement statistical approaches supporting Process Performance Qualification (PPQ), Continued Process Verification (CPV), Statistical Process Control (SPC), and process capability monitoring
• Support analytical method development, qualification, validation, and lifecycle management through statistically sound study design and data analysis
• Provide advanced statistical support for stability programs, shelf‑life estimation, comparability assessments, and global regulatory submissions
• Serve as the subject matter expert for exploratory data analysis, outlier assessments, regression modeling, multivariate analysis, and predictive modeling techniques
• Support investigations, deviations, CAPAs, quality risk assessments, and manufacturing troubleshooting activities through quantitative data analysis
• Drive adoption of advanced analytics, digital solutions, machine learning, and AI‑enabled statistical approaches across Technical Operations and Quality
• Author, review, and defend statistical content for regulatory submissions and health authority interactions
• Develop and deliver statistical training programs that increase statistical literacy and data‑driven decision‑making throughout the organization
• Continuously evaluate emerging industry trends, technologies, and best practices in CMC statistics and pharmaceutical manufacturing analytics

• Recognized expertise in statistical methodologies supporting pharmaceutical development, manufacturing, quality, and regulatory submissions
• Extensive knowledge of Design of Experiments (DOE), multivariate analysis, regression modeling, process capability analysis, statistical process control, and process validation methodologies
• Strong understanding of Continued Process Verification (CPV), Process Performance Qualification (PPQ), commercial manufacturing monitoring, and lifecycle process verification
• Deep understanding of analytical method validation, stability analysis, shelf‑life estimation, and comparability assessments
• Proficiency with statistical software platforms including JMP, Minitab, SAS, R, Python, and other advanced analytics tools
• Strong understanding of FDA, EMA, ICH, and global regulatory expectations related to CMC statistical analyses and process validation
• Knowledge of data integrity principles, including…