Role Summary
Sr. Non-Clinical Biostatistician supporting Vaccine R&D within the Translational and Early Development (TED) team. Leads statistical input for preclinical and non-clinical studies, collaborates with scientists and project managers, and ensures regulatory-compliant design, analysis, and reporting. Provides methodological and statistical direction for in vivo/in vitro studies, bioassay development, and biomarker research.
Responsibilities
- Act as the Lead Statistician providing support with minimal supervision on statistical requests and relevant statistical matters for the Preclinical and Non-clinical teams.
- Develop the digital mindset and data science capabilities of clients (communications, training, etc.).
- Support the digital evolution of the site within its scope of activity.
- Perform technology watch on data science topics and serve as the referent for the platform.
- Provide statistical input in the design of experiments for preclinical studies and/or clinically relevant bioassay development.
- Contribute to study setup to ensure data are adequately captured to address study objectives.
- Provide statistical support for experimental design, methodology, programming, and data analyses.
- Produce statistical analyses, write memos/reports, and communicate statistical conclusions to scientists.
- Accountable for statistical operations including sample size calculation, randomization plan (if applicable), and delivery of statistical methodology and reports.
- Ensure statistical content quality: select appropriate methodologies, drive risk assessment, interpret results, and perform exploratory/ad-hoc analyses as needed.
- Coordinate with internal and external stakeholders (R&D compliance, Project Manager, CROs, etc.).
- Under supervision, participate in project activities such as preclinical development plans, decision meetings, integrated analyses, dossier preparation, and publications.
- Represent TED and GBS in internal initiatives and present topics related to statistical activity.
Qualifications
- Education: Masterβs degree in Statistics with 4 years of industry experience OR PhD in Statistics/Biostatistics with internship in life science.
- Experience: Experience in Life Sciences industries is required; technical expertise in statistics, data science, and statistical modeling.
Skills
- Soft Skills: Good communication, ability to work in a multi-cultural environment, teamwork, eagerness to learn, good time management, autonomous.
- Statistical Tools: R, JMP, and other software (e.g., SAS or Python) are a plus.
- Language: Effective English in verbal and written communication.
Education
- Master's degree in Statistics with 4 years industry experience OR PhD in Statistics/Biostatistics with internship in life science.