Role Summary
Sr. Non-Clinical Biostatistician responsible for leading statistical support for preclinical/non-clinical studies within the TED team, providing design, analysis, and interpretation to ensure regulatory compliance and informed decision-making.
Responsibilities
- Act as the lead statistician providing statistical support with minimal supervision to the preclinical/non-clinical teams on statistical requests and matters.
- Develop the digital mindset and data science capabilities of clients; support digital evolution of the site.
- Perform technology watch on data science topics and serve as the referent for the platform.
- Provide statistical input in experimental design for in vivo/in vitro preclinical studies, CMC bioassay development, and related research.
- Contribute to study setup to ensure data are captured to address objectives.
- Provide statistical support for experimental design, methodology, programming, and data analyses; produce analyses, memos, and reports; communicate conclusions to scientists.
- Responsible for statistical operations including sample size calculations, randomization plan compliance, and delivery of statistical reports.
- Ensure statistical content is sound: select methodologies, assess risks, interpret results, and perform exploratory/ad-hoc analyses as needed.
- Coordinate with internal/external stakeholders (R&D compliance, project managers, CROs, etc.).
- Participate in project activities such as development plans, decision meetings, integrated analyses, dossier preparation, IND/CTD submissions, and publications under supervision.
- Represent TED/GBS in internal initiatives and present statistical topics internally and externally.
Qualifications
- Master's degree in Statistics with 4 years of industry experience OR PhD in Statistics/Biostatistics with life science internship.
- Experience in Life Sciences industries is required.
- Technical expertise in statistics, data science, and statistical modeling.
Skills
- Good communication; ability to work in a multi-cultural environment and in a team; autonomous and good time management.
- Experience with statistical tools: R, JMP; familiarity with SAS or Python is a plus.
- Effective English written and verbal communication.
Education
- Master's degree in Statistics (with 4 years of industry experience) or PhD in Statistics/Biostatistics.
Additional Requirements
- Experience in Life Sciences industries is mandatory.