Director CMC Statistics

Role Summary

Director, CMC Modeling & Advanced Statistics

What You Will Do

• Provide strategic and technical leadership in the design and implementation of kinetic modeling, Bayesian methods, and predictive analytics to support product and process characterization, stability modeling, and specification setting.
• Lead development and application of statistical/mathematical models to optimize manufacturing processes, evaluate product lifecycle and stability data, and support regulatory submissions.
• Champion the integration of Bayesian methods and modeling frameworks to enhance data utilization, manage uncertainty, and improve decision-making across the CMC lifecycle.
• Partner with cross-functional teams (Process Development, Analytical Sciences, Quality, Manufacturing, and Regulatory) to ensure modeling strategies are aligned with Amgen’s business and scientific objectives.
• Contribute to regulatory strategies by developing and defending modeling-based justifications in submissions and at regulatory authority interactions.
• Advance Amgen’s digital and data science strategy by incorporating machine learning, simulation, AI, and automation approaches into statistical workflows.
• Represent Amgen externally through scientific collaborations, publications, and conference presentations to establish thought leadership in CMC modeling.
• Train & guide other statisticians & data scientists in the use of innovative statistical approaches, including but not limited to kinetic, Bayesian, and predictive modeling

Qualifications

• Basic Qualifications:
  • Doctorate degree and 4 years of relevant biopharmaceutical industry experience OR
  • Master’s degree and 8 years of relevant biopharmaceutical industry experience OR
  • Bachelor's degree and 10 years of relevant biopharmaceutical industry experience
• In addition to meeting at least one of the above requirements, you must have at least 4 years experience directly managing people and/or leadership experience leading teams, projects, programs, or directing the allocation or resources.
• Preferred Qualifications:
  • Degree in Statistics, Biostatistics, Applied Mathematics, Engineering, or related quantitative field.
  • Deep expertise in kinetic modeling, Bayesian methods, and advanced statistical modeling techniques.
  • Strong track record of applying statistical modeling to CMC data, including stability, comparability, process characterization, and analytical method development.
  • Proficiency with statistical software (e.g., R, SAS, JMP, Minitab) and modeling tools (e.g., NONMEM, MATLAB, Stan, or similar Bayesian frameworks).
  • Demonstrated success influencing regulatory strategies through modeling-based approaches.
  • Proven ability to lead and develop technical talent in statistics and modeling.
  • Excellent oral and written communication skills, with ability to explain complex modeling approaches to both technical and non-technical audiences.
  • Experience working in cross-functional and global team environments.

Skills

• Kinetic modeling
• Bayesian statistics
• Predictive analytics
• Statistical programming (R, SAS, JMP, Minitab)
• Modeling tools (NONMEM, MATLAB, Stan, or similar)
• Cross-functional collaboration
• Regulatory strategy support

Education

• Doctorate or Master’s or Bachelor’s degree in a quantitative field as listed in qualifications