PRINCIPAL BIOSTATISTICIAN

Responsibilities:Participate and contribute to the development of new projects by providing expertise in design and statistical assumptions. Leads large projects involving complex project dynamics and ensuring alignment with strategic goals. Oversees data analysis initiatives; develops new methodologies and tools for data management. Participate in meetings with internal and external stakeholders in the discussion/defence of new study design contributing with data science expertise Participate and oversee in the development of Study Protocols by providing statistical input and data specifications. Design and oversee eCRF design and structure to ensure that it meets the specific requirements defined in the study protocol. Development and/or oversee Data Science Plan for assigned projects. Define or review randomization procedures and produce randomization lists. Development and review of Statistical Analysis Plans. Perform and/or supervise programming of tables, listings, figures, derived datasets, and statistical analyses according to agreed timelines and quality standards. Perform and/or supervise quality control of statistical output produced by other members of the department or external providers, including tables, listings, figures, derived datasets, and statistical analyses. Plan and perform statistical analysis (interim and/or final) in accordance with the Study Protocol and the Statistical Analysis Plan. Review and provide input in interpreting analysis results to clinical study report. Contribute to clinical development of plan preparation. Assist in performing/review sample size calculations. Participation in international multi-stakeholder advisory boards. Requirements:A bachelor’s degree in Life Science (Biology, Biotechnology, Biomedicine, Statistics...). Minimum 5 years of experience in biostatistics, with a focus on oncology clinical trials, especially in Phase III studies. Design of Phase I-IV clinical trials, basket, umbrella, and adaptive trials in oncology. Survival analysis methods (Kaplan-Meier, Cox models, hazard ratios, landmark analysis). Advanced statistical methodologies: Application of Bayesian methods and predictive modeling in oncology. Statistical analysis of biomarker data and precision medicine. Experience with patient-reported outcomes (PROs) and composite endpoints. Proficiency in SAS and R for advanced statistical analysis. Experience with CDISC standards (SDTM, ADaM) and dataset validation for regulatory submissions. Ability to translate complex statistical concepts for clinical, executive, and regulatory teams. Experience in writing and reviewing protocols, clinical study reports, and scientific publications. Presentation skills to defend trial designs and statistical analyses before medical, regulators and internal committees. Leadership in cross-functional teams (medical, regulatory, data management, and programming). Mentorship and supervision of junior statisticians and biostatistics teams Experience with real-world evidence (RWE) and real-world data (RWD) analysis in oncology is a plus. Knowledge of decentralized clinical trials (DCTs) and innovative trial methodologies. Familiarity with medical imaging analysis and omics data in oncology. Ability to manage multiple projects simultaneously in a highly regulated environment with tight deadlines.