Hiring Senior Manager/Associate Director Biostatistician for Small Pharmaceutical company in San Francisco bay area.
Responsibilities
• Lead in product / indication level tasks and ensure statistical integrity; contribute strategically to the supporting projects from statistics perspective
• Contribute in study level tasks from statistics perspective, including: Contribute in study design and sample size determination; Author/review statistics section in the protocol, SAP and DMC charter; Create/review study randomization files; Develop TLG shell and specification Review CRFs and other study documentations; Active participation in study related meetings
• Works collaboratively within biometrics teams and with cross-functional teams to meet product deliverables and timelines for statistical data analysis and reporting
• Ensure statistical integrity of deliverables; provide statistically sound scientific methodology input to meet project objectives and regulatory statistical and data requirements
• Independently conduct analyses suggested by the data; Propose new/novel statistical methodological approaches to improve the efficiency and sensitivity of study results
• Contribute in developing standards and research in advanced statistical methodologies
• Author/review regulatory documents or scientific publications
• Mentor junior team members
Requirements
• Masters/PhD in Statistics or Biostatistics with a minimum of 8 years of post-graduate experience in the clinical trials setting (min 5 years for PhD), preferably in the pharmaceutical industry, either with a sponsor or a CRO
• Proven experience as product lead statistician and contribute in strategy discussion in cross functional settings
• Demonstrated ability to manage multiple products and studies with prioritization
• Experienced in study level work including authoring SAP and TFL specification
• Familiar with ICH guideline, FDA / EMA / other regulatory authority guidance
• Solid understanding of mathematical and statistical principles; Experience in statistical methods analyzing longitudinal data is preferred
• Good communication and interpersonal skills, with the ability to translate statistical concept to program / study strategies
• Detailed-oriented with organization, problem solving and prioritization skills; demonstrated the ability to prioritize and complete multiple tasks according company timeline
• Familiar with SAS and R; preferably with knowledge in CDISC including SDTM, ADaM, and controlled terminologies