Executive Director, CMC Quantitative Sciences

The Role: 

Moderna is seeking an Executive Director, CMC Quantitative Sciences to build and lead a centralized data analytics and statistical sciences function that supports all of CMC (Technical Development, Manufacturing, Quality, CMC Regulatory, et al.). The role involves leading a dedicated team of statisticians, data scientists and engineers, with overall accountability for defining and delivering a robust data analytics, process modeling, and statistical sciences capability in support of Moderna’s mRNA portfolio.

As the lead for this core capability, this person will partner across CMC and with Digital to guide the scientific data strategy, architecture, and governance, and enable efficient development and manufacturing process analysis and decision-making tools. Overall, the focus is on facilitating efficient sharing, consumption, and interpretation of data to both define optimal control strategies and drive continuous improvement throughout the CMC product lifecycle.

The team functionally reports into the Technical Development organization and will operationally report into the various manufacturing business units within CMC, supporting process monitoring and manufacturing data needs, all the while building new data science, statistics, and modeling capabilities for the future. The Technical Development organization within CMC is comprised of scientists, engineers, and problem solvers that develop and implement the most innovative, advanced, and robust platform processes and analytical technologies to deliver Moderna’s medicines.

The role is based in Moderna’s Moderna Technology Center campus in Norwood, MA, but may require presence at the Cambridge site as well as occasional travel to manufacturing and analytical testing sites within the network as needed. 

Here’s What You’ll Do:  

• Provide team leadership in developing and delivering the end-to-end data analytics and statistical science core capability that supports Moderna’s CMC development lifecyle, from process development through GMP commercial manufacturing and regulatory approval.

• Partner with all CMC functions to assess needs, identify opportunities, and implement tools and approaches that enable access and use of data, including machine learning, multivariate modeling, process trending, process monitoring, design of experiments, etc.

• Provide team leadership and organizational direction toward best practices that enable efficient sharing, consumption, and interpretation of data throughout the CMC product lifecycle

• Advise and influence organization-wide data governance strategies, including architecture of software platforms, data standards, knowledge management, and data-related business processes applicable across the CMC organization

• Build and mentor a dedicated, high-performing team of internal subject matter experts across a broad spectrum of data analytics, mathematical sciences, and CMC statistics disciplines, consolidating expertise for data-driven decision making and the development of fundamental data analytics workflows and process models.

• Establish and evolve standards and practices for the management of analytics pipelines, modeling, analysis, visualization, and presentation of data

• Maintain routine process and platform monitoring tools and methodologies supporting clinical and commercial manufacturing

Here’s What You’ll Bring to the Table: 

• PhD degree in Chemical/Biochemical Engineering, Statistics, Mathematics or a related discipline with technical experience relevant to areas within the quantitative sciences disciplines.

• Prior experience with quantitative sciences disciplines and technologies that support cGMP, process development/ scale-up and methods /process validation, continuous process verification, and preparation of regulatory submissions, is preferred, with 15+ years of industry experience in pharmaceutical development and/or manufacturing sciences and technology.

• Prior experience in a fast-paced environment with demonstrated ability to leverage external collaborations with industry and academic partners

• Demonstrated understanding of the development lifecycle from R&D through commercialization, including an understanding of the interdependencies of functional groups.

• Strong technical/scientific experience in product development and commercialization

• Experience in late-stage development and project management, including strong communication skills and ability to operate effectively in ambiguity by anticipating and balancing needs of multiple stakeholders

• Demonstrated experience developing and implementing an innovative data and analytics solutions

• Skilled at facilitating teams and building consens