CMC Statistician Intern at Prime Medicine, Inc. in Cambridge, MA

Summary: Prime Medicine is a leading biotechnology company dedicated to creating innovative gene editing therapies. The CMC Statistician Intern will contribute statistical support across various analytical processes, providing insights that inform development decisions in the context of clinical development. Responsibilities: - Apply statistical methods (including design of experiments, DoE) to support method development, qualification and validation activities, including assessments of accuracy, precision, linearity, range, and robustness - Summarize and interpret data in a manner suitable for inclusion in regulatory-facing documentation - Support statistical analysis of process development data to identify critical process parameters and understand sources of variability - Contribute to DoE planning and analysis in collaboration with process development scientists - Analyze stability data using ICH-aligned statistical approaches, including regression modeling and degradation rate estimation - Contribute to the development and maintenance of statistical process control (SPC) techniques for monitoring reference standard and critical reagent performance - Support shelf-life and retest period calculations and help maintain stability tracking tools - Apply statistical methods to support specification setting for drug substance and drug product, including tolerance interval calculations and acceptance criteria justification - Assist in statistical review of release and characterization data across development-stage lots - Prepare clear, well-documented statistical analyses suitable for inclusion in technical reports, regulatory submissions, and IND-enabling packages - Work within a GxP-aware environment; gain practical exposure to documentation standards and data integrity principles relevant to early-phase pharmaceutical development Required Qualifications: - Enrollment in a BS program in Statistics, Biostatistics, Mathematics, Chemical Engineering, or a related quantitative discipline; junior or senior standing preferred - Solid foundation in applied statistics, including regression, hypothesis testing, variance analysis, and tolerance or confidence intervals - Proficiency in at least one statistical computing environment (R, Python, JMP, or Minitab) - Ability to communicate quantitative results clearly, both in writing and in conversation with scientific collaborators Preferred Qualifications: - Coursework or project experience in experimental design (DOE) or statistical process control - Familiarity with ICH guidelines relevant to CMC statistics (e.g., Q2(R2), Q8, Q1E) - Prior lab, co-op, or research experience in a pharmaceutical, biotech, or academic drug development setting - Exposure to GxP environments or data integrity principles, even in an academic or co-op context Required Skills: Applied statistics, Regression, Hypothesis testing, Variance analysis, Tolerance intervals, Confidence intervals, Statistical computing environment - R, Statistical computing environment - Python, Statistical computing environment - JMP, Statistical computing environment - Minitab, Design of experiments (DoE), Statistical process control (SPC), ICH guidelines - Q2(R2), ICH guidelines - Q8, ICH guidelines - Q1E, GxP practices