Summary
Kasey Jones is a Data Scientist with 11 years of experience applying statistical modeling, machine learning, and data engineering to drive product engagement and research insights, currently contributing at Meta. She has deep applied analytics roots from RTI International—implementing transfer learning for image recognition, building agent-based models for NIH/CDC, and optimizing large-scale co-occurrence computations. Earlier roles at Booz Allen and Allegis highlight her ability to turn analytics into interactive tools and automated workflows (R Shiny, VBA, SAS macros) that improve decision-making and operational efficiency. With dual MS degrees in Applied Mathematics and Analytics and a BS in Mathematics Education, she combines rigorous quantitative training with a knack for translating complex models into usable products. Based in Pittsboro, NC, Kasey pairs product-focused experimentation with research rigor, often bridging prototype ML proofs-of-concept into production-ready solutions.
11 years of coding experience
5 years of employment as a software developer
Master of Science (M.S.), Analytics, Master of Science (M.S.), Analytics at Institute for Advanced Analytics
Bachelor of Science (BS), Mathematics Teacher Education, 3.95, Bachelor of Science (BS), Mathematics Teacher Education, 3.95 at Western Carolina University