Senior Manager, Biostatistics

Job Responsibilities

• 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.
• 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.
• Prior experience in oncology clinical development (preferred).