The Senior Manager, Biostatistics acts as statistical study lead; provides technical input and biostatistical support on the design and conduct of clinical studies; participates in the evaluation, interpretation, and reporting of study results; performs statistical analyses; provides timely support to the project teams on all statistical matters
Responsibilities:
Lead in study level tasks, ensuring statistical integrity; contribute strategically to the supporting projects from statistics perspective.
Contribute to study level tasks from statistics perspective, including study design and sample size determination, protocol statistics section, SAP and DMC charter; Review study randomization files; Develop TFL 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
Independently conduct analyses suggested by the data; Propose new/novel statistical methodological approaches to improve the efficiency and sensitivity of study results
Contribute to developing standards and research in advanced statistical methodologies
Review regulatory documents or scientific publications
Requirements / Qualifications
PhD in Statistics or Biostatistics with a minimum of 3 years (min 6 years for Master's degree) of post-graduate experience in the clinical trials setting in the pharmaceutical industry
Experienced in NDA / BLA / MAA activities as a contributor from statistics perspective and direct involvement in regulatory interaction is preferred
Experienced as or is capable to act as study lead statistician and contribute to strategy discussion in cross functional settings
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
Detailed-oriented with organization, problem solving and prioritization skills; demonstrated the ability to prioritize and complete multiple tasks according to company timeline
Familiar with SAS and R; preferably with knowledge in CDISC including SDTM, ADaM, and controlled terminologies