Statistician, CMC (Chemistry, Manufacturing, and Controls)

More than one million people in the United States today are fighting blood cancer. While a traditional allogeneic stem cell transplant has been the best hope for many, the transplant itself can prove fatal or lead to serious conditions, such as graft vs. host disease. Orca Bio is a commercial-stage biotechnology company redefining the transplant process by developing next-generation cell therapies with the goal of providing significantly better survival rates with dramatically fewer risks. With our purified, high-precision cell therapies we hope to not only replace patients' blood and immune systems with healthy ones, but also restore their lives. Position Summary: We are seeking a skilled Statistician to join our CMC organization and provide statistical leadership across analytical method development, validation, comparability, and product characterization activities. The successful candidate will partner closely with Analytical Development, Process Development, and Validation teams to design studies, analyze complex data (including non-normal distributions common in biologics assays), and translate results into clear, regulatory-defensible conclusions that support process and product decisions across the product lifecycle. In this role, you will provide hands-on statistical expertise across the full product lifecycle, from early analytical method development through commercial manufacturing, ensuring compliance with ICH, FDA, and EMA guidance. \n Essential Duties & Key

Responsibilities 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. Experience & Education 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. \n $100,000 - $160,000 a year \n The anticipated annual salary range for this job is based on prior experience in