Sas Developer Remote Jobs in California (NOW HIRING)

• Design and execute comparability assessments for process changes, site transfers, scale- up/scale-down activities, and reference standard qualification, utilizing equivalence testing, quality range methods, and mixed-effects models to establish pre-specified acceptance criteria.
• Develop and apply tolerance interval methodologies (parametric, non-parametric, and distribution-free approaches) to establish specifications, in-process control limits, and shelf- life/stability ranges across the product lifecycle.
• Conduct Bland-Altman analysis and method-agreement/method-transfer evaluations to assess bias, limits of agreement, and comparability between analytical platforms, instruments, and laboratories.
• Provide statistical support for analytical method validation and verification, including accuracy, precision, linearity, range, and robustness studies, with particular expertise in handling non- normal and skewed data through transformation strategies and non-parametric methods.
• Author and review statistical sections of validation protocols, reports, and summary statistics packages suitable for regulatory submissions (BLA/MAA/NDA, CTD Module 3) and responses to health authority queries.
• Develop, validate, and maintain statistical code and templates (R, SAS, JMP, Python) to ensure consistency, traceability, and reproducibility of analyses; stay current with ICH, FDA, and EMA guidance on comparability, analytical procedures, and statistical methods.
• Collaborate with Analytical Development, Process Development, QC, and Regulatory Affairs to design fit-for-purpose experimental designs (DOE), sampling plans, and risk assessments while communicating statistical concepts clearly to non-specialist stakeholders.

• B.S., M.S., or Ph.D. in Statistics, Biostatistics, Applied Mathematics, or a related quantitative field (or equivalent experience).
• 6+ years (B.S.), 3+ years (M.S.), or 1+ years (Ph.D.) of relevant industry experience applying statistics within a CMC, analytical development, or QC environment in biotech/pharma.
• Demonstrated hands-on experience with comparability assessment methodologies for biologics or small molecules, tolerance interval construction (parametric and non-parametric), and Bland- Altman/method-comparison techniques.
• Demonstrated experience providing statistical support for analytical method validation, including strategies for non-normal/non-Gaussian data, robust statistics, and bootstrapping methods.
• Proficiency in a statistical programming language (JMP preferred; R, SAS, Minitab, or Python also relevant).
• Working knowledge of relevant ICH Q2(R2), Q14, FDA, and EMA guidance related to analytical procedures, comparability, and specification setting.
• Strong written and verbal communication skills with ability to explain statistical reasoning to cross-functional, non-statistical audiences.
• Excellent attention to detail and ability to manage multiple concurrent projects in a fast-paced, highly regulated environment.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.