CMC Statistics Director

Vertex Pharmaceuticals•Boston, MA

17h•Hybrid

About The Position

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.

Requirements

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 ALCOA+ requirements, and their application in regulated environments
Strong leadership, influencing, stakeholder management, and change management capabilities
Exceptional written, verbal, and presentation skills with the ability to communicate effectively across technical and executive audiences
Ph.D. in Statistics, Biostatistics, Industrial Engineering, Applied Mathematics, Data Science, or related quantitative discipline with 10+ years of relevant industry experience; or M.S. in Statistics, Biostatistics, Industrial Engineering, Applied Mathematics, Data Science, or related quantitative discipline with 12+ years of relevant industry experience
Demonstrated experience supporting CMC development, process validation, manufacturing, quality operations, and regulatory submissions in a pharmaceutical or biotechnology environment

Nice To Haves

Experience applying statistical methodologies across biologics, cell and gene therapy, small molecules, and/or combination products preferred
Demonstrated success establishing statistical best practices, governance models, and capability-building programs within regulated environments
Experience leveraging advanced analytics, machine learning, digital manufacturing, and AI-enabled solutions preferred
Experience supporting global regulatory inspections, responses, and health authority interactions is strongly preferred

Responsibilities

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