Senior Manager, Biostatistics

Serve as the study biostatistician for assigned clinical oncology studies, contributing to the development and execution of statistical strategies, study designs, and analyses under the guidance of senior biostatistics leadership. Collaborate closely with multidisciplinary project teams to ensure timely communication and alignment of objectives. Help identify and implement solutions to statistical and data analysis issues related to clinical trials and regulatory submissions. Author and contribute to key statistical documents and outputs, including protocol statistical sections, SAPs, and TLF shells, with review by senior biostatisticians. Review study-related documents and review/validate vendor deliverables, including CDISC data specifications and TLF/analysis outputs. Work with internal programmers to support regulatory requests, DSUR/IB updates, and ad-hoc analyses as needed. Participate in the internal sponsor review of ongoing clinical data. Support AI initiatives led by the Biometrics AI lead that enhance quality control and operational efficiency. Requirements Ability to work on site in our San Diego Office working Hybrid Work Schedule. Willing to travel approximately 10% of the time. Evening and weekend work will be involved. Strong interpersonal and communication skills, with the ability to collaborate effectively with cross‑functional stakeholders. Able to function in a highly regulated environment and to adhere to all RayzeBio guidelines and SOPs. Proficiency with statistical programming tools (e.g., SAS and/or R) and working knowledge of CDISC standards (SDTM/ADaM), with the ability to review and interpret key statistical outputs. Experience working with vendors to help ensure the quality, timeliness, and compliance of biometrics deliverables. Solid working understanding of GCP, ICH guidelines, and regulatory requirements. Advanced degree in Statistics or Biostatistics (PhD or MS). 3+ years (PhD) or 6+ years (MS) of biostatistics experience in the pharmaceutical/biotech industry. Familiarity with AI‑enabled tools to improve productivity and work efficiency. Exposure to innovative/novel clinical trial designs (e.g., adaptive designs). Working knowledge of Bayesian methods in a clinical development setting. #J-18808-Ljbffr