Scientist CPV, Comparability, and Statistics

Apply advanced statistical methods including SPC, DOE, regression, and multivariate analysis to support data driven decisions Partner cross functionally with MS&T, Process Development, Manufacturing, and Quality teams to support investigations, deviations, and CAPA activities perform statistically robust analysis to support the update of process monitoring limits perform statistical comparability assessments to support process and product changes such as scale up, site transfers, or optimization activities Identify opportunities to improve process robustness through advanced analytics, digital tools, and continuous improvement initiatives Contribute to regulatory submissions and provide statistical justification during audits and inspections Analyze process data to identify trends, variability, and potential process drift support of Continued Process Verification (CPV) programs to monitor manufacturing performance

CSL Behring is a global biotherapeutics leader driven by our promise to save lives. Focused on serving patients’ needs by using the latest technologies, we discover, develop and deliver innovative therapies for people living with conditions in the immunology, hematology, cardiovascular and metabolic, respiratory, and transplant therapeutic areas. We use three strategic scientific platforms of plasma fractionation, recombinant protein technology, and cell and gene therapy to support continued innovation and continually refine ways in which products can address unmet medical needs and help patients lead full lives.

CSL Behring operates one of the world’s largest plasma collection networks, CSL Plasma. Our parent company, CSL, headquartered in Melbourne, Australia, employs 32,000 people, and delivers its lifesaving therapies to people in more than 100 countries.

• A Master’s degree or PhD in Statistics, Engineering, Biostatistics, or a related discipline

• Strong expertise in statistical analysis, and data interpretation

• Hands on experience with statistical tools such as JMP, Minitab, R, or Python

• Solid knowledge of GMP and regulatory expectations

• Experience supporting comparability studies and product lifecycle management (preferred)

• The ability to communicate complex statistical concepts clearly to cross functional stakeholders