Sr. Statistician – Chemistry, Manufacturing, and Controls (CMC)

MSD

6d•Hybrid

About The Position

Under the general supervision of a senior staff member in Center for Mathematical Sciences (CMS), the incumbent is responsible for the statistical analysis and evaluation of data to meet the needs of our company’s Manufacturing Division. The individual will, through consultation with employees and teams, provide statistical expertise on experimental design, and the evaluation and interpretation of data. As required, the incumbent will evaluate data for submission to regulatory agencies and pharmacopoeia.

Requirements

Bachelor of Science (BS) in statistics or related field with ten (10) years of required experience, OR Master of Science (MS) in statistics or related field with five (5) years of required experience, OR PhD in statistics or related field with no required experience. Please note: Coursework and/or experience should include industrial statistics (DOE, SPC, regression, general linear models, and multivariate methods, computer programming)
A statistician experienced working in a pharmaceutical company dedicated to supporting vaccine manufacturing, emphasizing critical thinking, domain knowledge, and scientific partnership.
Demonstrated experience supporting Chemistry, Manufacturing, and Controls (CMC) activities for drug substance and drug products, including stability studies, comparability assessments, process validation, and control strategy development aligned with ICH guidelines
Working experience with Bayesian statistical framework
Background in mammalian cell culture and yeast fermentation
Proficient in live virus potency (plaque assays, TCID50, qPCR/dPCR) and recombinant protein analytics (ELISA, HPLC/UPLC).
Excellent statistical computing skills with substantial experience in at least two of the following statistical software packages: SAS, R, JMP, Minitab.
Hands-on experience with Design of Experiments (DoE), Analysis of Variance (ANOVA), Analysis of Covariance (ANCOVA), mixed-effects models, response surface methods, process capability, Statistical Process Control (SPC), Continued Process Verification (CPV), tolerance intervals, equivalence/non-inferiority testing, and Monte Carlo simulations
Strong consulting skills with the ability to work independently and collaboratively across cross-functional teams.
Excellent oral and written communication skills; able to explain statistical concepts and results to non-statisticians and influence decision-making
Proven leadership with advanced problem-solving and decision-making skills; adept at managing multiple projects, meetings, time, and priorities
Ability to think originally and creatively to develop practical, high-impact solutions and to persuade and motivate others toward adoption
Accountability
Bayesian Statistics
Business Intelligence (BI)
Capability Analysis
Cell-Based Assays
Cell Cultures
Computer Programming
Control Charts
Data Analysis
Database Design
Data Engineering
Data Modeling
Data Science
Data Visualization
Machine Learning (ML)
Mammalian Cell
Mammalian Cell Culture
Manufacturing
Manufacturing Processes
Manufacturing Support
Mixed Models
Response Surface Methodology
SAS Language
Software Development

Responsibilities

Partner with manufacturing teams to define clear objectives, success criteria, and decision points for process studies; select fit-for-purpose tools (e.g., ANOVA, ANCOVA, mixed-effects models).
Design and analyze experiments using Design of Experiments (DoE) to understand, optimize, and qualify/validate vaccine manufacturing processes and analytical methods.
Support scale-up, technology transfer, and comparability with sound protocols, acceptance criteria, and statistical justifications.
Analyze stability and shelf-life studies aligned with International Council for Harmonisation (ICH) guidance; perform degradation modeling, trend analysis, and shelf-life estimation using regression, mixed-effects models, and tolerance/prediction intervals.
Establish and maintain ongoing monitoring using Statistical Process Control (SPC) and Continued Process Verification (CPV) for Critical Quality Attributes (CQAs) and Critical Process Parameters (CPPs); implement control charts (e.g., X-bar/R, Individuals-Moving Range), capability analysis (Cp/Cpk/Pp/Ppk), and nonparametric trend tests as needed.
Troubleshoot issues, including Out-of-Specification (OOS) and Out-of-Trend (OOT) results, using data analysis, root-cause hypotheses, and targeted confirmation studies; apply multivariate methods (e.g., PCA, PLS) and Monte Carlo simulations for risk and sensitivity analysis.
Translate results into practical recommendations for setpoints, ranges, sampling plans, and control strategies; based on risk and uncertainty.
Develop reproducible, auditable analysis using good manufacturing/documentation practices.
Prepare clear statistical content for Chemistry, Manufacturing, and Controls (CMC) documentation; assist with regulatory queries using sound statistical rationales.