The Senior Manager, Biostatistics acts as a 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 a statistical perspective.
- Contribute to study level tasks from a statistical perspective, including study design and sample size determination, protocol statistics section, SAP, and DMC charter.
- Review study randomization files.
- Develop TFL shell and specifications.
- Review CRFs and other study documentation.
- Participate actively in study-related meetings.
- Collaborate 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 or 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 (or 6 years for Master’s degree) of post-graduate experience in the clinical trials setting within the pharmaceutical industry.
- Experience in NDA / BLA / MAA activities as a contributor from a statistical perspective and direct involvement in regulatory interactions is preferred.
- Experience as or capability to act as a study lead statistician and contribute to strategy discussions in cross-functional settings.
- Experience in study-level work including authoring SAP and TFL specifications.
- Familiarity with ICH guidelines, FDA / EMA / other regulatory authority guidance.
- Solid understanding of mathematical and statistical principles.
- Detail-oriented with strong organization, problem-solving, and prioritization skills; demonstrated ability to manage multiple tasks according to company timelines.
- Proficiency with SAS and R; preferably with knowledge of CDISC standards including SDTM, ADaM, and controlled terminologies.