Emma Mendelsohn is an senior environmental scientist with over 10 years of experience in environmental data analytics, toxicology, risk assessment, and project management. She specializes in leveraging environmental data and strategic workflow design to drive evidence-based decision making. Her expertise spans conventional and algorithmic risk assessment approaches, with a focus on legacy and emerging contaminants, climate-sensitive communicable diseases, and biological threats to agriculture.
Emma has led multidisciplinary teams on projects for private sector clients and federal agencies, including the U.S. Environmental Protection Agency (USEPA) and the Department of Homeland Security (DHS). She provides expertise in advanced quantitative methods, including multivariate and hierarchical machine learning, Bayesian statistics, and artificial intelligence, to extract insights and predictions from spatially and temporally dynamic data. Emma is skilled in developing scalable, cloud-based infrastructure for data analysis and project pipeline management, ensuring reproducibility and seamless implementation. Additionally, her work emphasizes risk communication, stakeholder engagement, and consensus-building to translate data products into actionable outcomes.