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Principal Biostatistician – Chemistry, Manufacturing and Control
Clinical Outcomes SolutionsBiostatistician supporting CMC projects across the drug development lifecycle. Engaging with teams to analyze manufacturing data ensuring product quality and compliance.
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in statistical modeling and analysis, particularly using R programming and linear mixed models, to support CMC-related studies in the pharmaceutical or biotechnology sectors. Collaborates effectively with cross-functional teams to ensure compliance with regulatory guidelines and internal standards.
Highest-signal resume keywords
PhD In BiostatisticsR ProgrammingLinear Mixed ModelsBayesian StatisticsStatistical Modeling
ATS Keywords
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Hard Skills
Statistical ModelingData VisualizationSimulationsLinear Mixed ModelsStatistical TransformationsStatistical AnalysisBayesian MethodsProcess ValidationAnalytical Method ValidationFormulation Development
Soft Skills
Excellent CommunicationCollaborative Skills
Industry Keywords
CMCFDAEMAICHPharmaceuticalBiotechnology
About the role
Key responsibilities & impact- Provide statistical support for CMC-related studies, including formulation development, stability studies, process validation, and analytical method validation.
- Collaborate with cross-functional teams, including analytical scientists, process engineers, and regulatory affairs, to develop and implement appropriate statistical strategies.
- Design and analyze experiments using linear mixed models, particularly for stability and variability analyses.
- Perform statistical modeling, data visualization, and simulations using R programming.
- Experience with Bayesian methods preferred.
- Ensure quality and compliance with internal standards and regulatory guidelines (e.g., FDA, EMA, ICH).
Requirements
What you’ll need- PhD in Biostatistics, Statistics, or a related quantitative discipline.
- A strong interest in supporting CMC or related manufacturing/analytical projects in a pharmaceutical or biotechnology setting.
- Strong proficiency in R programming for statistical modeling, analysis, and visualization.
- Solid understanding and practical application of linear mixed models.
- Excellent communication and collaborative skills to work effectively across teams.
- Exposure to or hands-on experience with Bayesian statistics and its application in industrial settings.
- Familiarity with a wide variety of statistical transformations and distributions, appropriate for CMC data.
Benefits
Comp & perks- Consistent training
- Development
- Support