Sr. Non-Clinical Biostatistician

Role Summary

Senior/lead statistician for preclinical and non-clinical work within the TED (Translational and Early Development) team, providing statistical support for R&D activities including pre-clinical studies, bioassay, and biomarker research. Responsible for methodological and statistical aspects of non-clinical studies, influencing study design, analysis, and regulatory-compliant reporting. Works under supervision of TED senior managers and collaborates with scientists, project managers, and external partners as needed.

Responsibilities

• Act as the lead statistician and provide support with minimal supervision on statistical requests across the preclinical/non-clinical teams.
• Develop the digital mindset and data science capabilities of clients (communications, training, etc.).
• Support the digital evolution of the site within scope of activity.
• Perform technology watch on data science topics and serve as the referent for the data science platform.
• Provide statistical input in the design of experiments for in vivo/in vitro preclinical studies and/or clinical analytical bioassay development.
• Contribute to study setup to ensure data are adequately captured to address objectives.
• Provide statistical support for experimental design, methodology, programming, and data analyses; prepare memos/reports and communicate conclusions to scientists.
• Accountable for statistical operations including sample size calculation, randomization plan (if applicable), and quality/delivery of statistical reports.
• Accountable for statistical content: select methodologies, assess risk, interpret results, perform exploratory and ad-hoc analyses.
• Coordinate with internal and external stakeholders (R&D compliance, Project Manager, CROs, etc.).
• Under supervision, participate in preclinical development planning, decision-making meetings, integrated analyses, dossier preparation, IND/CTD submissions, and publications follow-up.
• Represent TED/GBS in internal initiatives and present statistical topics internally and externally.

Qualifications

• Required: Master's degree in Statistics with 4 years of industry experience OR PhD in Statistics/Biostatistics with internship in life science.
• Required: Experience in Life Sciences industries.
• Required: Technical expertise in statistics, data science, statistical modelling, etc.
• Preferred: Experience with statistical programming tools such as R and JMP; knowledge of SAS or Python is a plus.

Skills

• Good communication skills
• Ability to work in a multi-cultural environment
• Team-oriented with effective collaboration
• Eager to learn and open-minded
• Good time management
• Autonomous

Education

• Master's degree in Statistics with 4 years industry experience OR PhD in Statistics/Biostatistics with internship in life science