Director, Safety Data Science

Role: Lead the development and deployment of advanced data analytics, AI, and machine learning solutions within Global Medical Safety to enhance safety decision-making and operational efficiency. Responsibilities: shape strategy for safety analytics and AI, lead project teams to deliver scalable analytical tools, develop data pipelines, models, dashboards, and analytical applications, and promote adoption of emerging technologies. Provide scientific and technical leadership across safety analytics domains, including predictive safety, risk assessment, and quality monitoring. Collaborate with cross-functional teams and senior stakeholders; mentor analytics professionals; support strategic initiatives. Qualifications: PhD preferred (or Master's with extensive experience) in Statistics, Data Science, Bioinformatics, or related fields; significant experience in healthcare analytics, medical safety, or pharmacovigilance; proven ability to lead end-to-end analytical projects and teams. High-Value: expertise in AI/ML, predictive modeling, natural language processing, and large language models; proficiency in Python, R, SQL; experience with cloud architectures and MLOps; supporting safety and real-world evidence data environments. WorkSetup: Locations include Horsham, PA, and Titusville, NJ; specifics not provided but likely hybrid or onsite given the roles' seniority and technical nature.