Marissa received her PhD from the University of Chicago in Chemistry, where she worked on modeling actin filament dynamics using coarse-graining of atomistic-level simulations to understand and extrapolate the effects of longer time-scale movements. In 2013, she received the Jane Coffin Childs postdoctoral fellowship to study the structure and functional mechanisms of ESCRT proteins, which participate in membrane remodeling. After two years, Marissa left academia to pursue a career in data science. First as a consultant, she used the same kinds of statistical modeling techniques that she had used in her PhD to solve business problems in a range of fields, spanning biopharmaceuticals, gaming, and marketing attribution. In 2016, she joined Degreed, a SAAS startup focused on helping people develop and measure skills, where she worked on recommendation systems and on using machine learning and data science to understand the landscape of learning. At Recursion, Marissa has found a way to return to her science roots, while still using cutting-edge data science tools to solve problems that have significant impact on people’s lives.
Outside of work, Marissa enjoys training in Muay Thai, gardening, reading (everything from Stoicism to fiction, from the psychology of behavioral change to machine learning), complicated board games, and anything with her family.
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