Principal Statistician - Early Phase - Fully home based (remote anywhere in Europe) Sponsor Dedicated

Overview As Principal Statistician at Syneos Health, you will lead biostatistics activities for early-phase projects, mentoring junior statisticians and guiding study design and analysis. You collaborate across sponsor teams to ensure robust SAPs, data handling, and regulatory readiness. You may serve as Lead Biostatistician on protocols and analysis results, and you will help drive timely, high-quality deliverables across complex trials. This role offers influence on study outcomes, interdisciplinary collaboration, and exposure to regulatory interactions within a global, mission-driven CRO.

Verantwortungsbereiche Lead and mentor biostatistics personnel across projects Develop and review SAPs and analysis plans, including tables, listings, and figures Oversee statistical aspects of protocols and randomization schedules Review CRFs, data management plans, and databases for quality and completeness Provide statistical programming support and ensure QC of deliverables Lead or contribute to complex projects such as submissions or integrated analyses Participate in DSMB/DMC activities as independent or voting statistician Ensure regulatory guideline compliance (ICH, SOPs) and maintain documentation for inspections Support business development activities through proposals and sponsor meetings Zentrale Anforderungen Graduate degree in biostatistics or related discipline Extensive experience with clinical trials and ability to lead multiple programs Proficiency in R programming

Strong knowledge of statistical design, analysis, and regulatory guidelines Experience across lifecycle of trials from protocol to CSR Experience with regulatory submissions preferred Excellent written and verbal communication skills English proficiency (read/write/speak) Ability to manage multiple projects and meet timelines PhD/MS in statistics or related discipline (stated preference) leadership effective communication collaboration R programming SAS statistical design and analysis