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Eacademy Sanofi

Senior Lead Clinical Modeler

Eacademy Sanofi, Marcy, New York, United States

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The job offer is accessible to all, regardless of gender. Job title:

Senior Lead Clinical Modeler Location: Marcy l’Etoile Home office possible in respect with Sanofi global policy. Occasional travel required Job type: Permanent, Full time About the job

The Global Biostatistical Sciences department at Sanofi Vaccines is seeking to hire a highly talented mathematical, statistical and computational modeling scientist to support its Vaccines R&D portfolio. Modeling & simulation brings unique opportunities to inform decision making and streamline the various steps of vaccines discovery and development. Are you ready to shape the future of vaccines development? Sanofi is committed to speeding up vaccines discovery and development to continuously improve public health and patients’ life. Your talent could be of deep value in helping our project teams accelerate progress through modelling. About Sanofi

We’re an R&D-driven, AI-powered biopharma company committed to improving people’s lives and delivering compelling growth. Our deep understanding of the immune system – and innovative pipeline – enables us to invent medicines and vaccines that treat and protect millions of people around the world. Main responsibilities: Develop complex quantitative vaccine models in close collaboration with multidisciplinary teams to inform and optimize vaccine development Develop and run in-silico clinical trials in virtual individuals to de-risk, optimize, and accelerate vaccines development Predict the future through simulations – e.g., Lead the use of models to predict the future trajectory of disease during vaccine trials Lead the continuous update and refinement of models based on new data and insights from research and real-world results Assessment and prioritization of modeling strategic contribution to ensure quality and timely impact of modeling and simulation work packages Clear communication of modeling results to stakeholders, including decision makers Bring the implementation of scientific and technological innovations in the area of disease and vaccines impact modeling About you

Education: Ph.D. degree in a quantitative scientific field such as epidemiology, biostatistics, immunology, computational systems biology, or applied mathematics Experience: 7+ years experience in pharmaceutical clinical research with at least 3 years modelling experience Soft and technical skills: Mathematical and Statistical Modeling: Demonstrated evidence of comprehensive understanding of mathematical modeling techniques Epidemiology: Established knowledge of infectious disease epidemiology Computer Programming: Demonstrated proficiency in programming languages for implementing models and in AI/ML Demonstrate project management skills, customer orientation and influencing skills Build and maintain effective strategic working relationships with internal and external partners Identify, develop and implement novel methodologies and invest in expanding expertise across clinical, regulatory, and commercial domains Demonstrate ability to stay current with the latest research and adapt to new technologies and methodologies Ability to work independently and collaborate effectively in interdisciplinary teams Communication: Ability to effectively communicate model results and recommendations to statistical, clinical, and senior management colleagues Why choose us?

Bring the miracles of science to life alongside a supportive, future-focused team Collaborate within multidisciplinary teams, leverage cutting-edge technologies, bring innovative modelling solutions to shape the future of vaccines development Benefit from a well-thought-out benefits package that rewards your contribution and commitment Pursue your career at an attractive location and experience our modern working environment and benefit from hybrid, flexible working time models At Sanofi, we provide equal opportunities to all regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, protected veteran status or other characteristics protected by law.

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