After Rachel obtained her Bachelor of Science degree in Biology from Furman University, she was a biological technician with the National Park Service in New Mexico and Texas before returning east to pursue technical skills in Geographic Information Systems. In 2017, she joined ORNL as a Post Bachelor’s Research Associate in the Geographic Information Sciences group (now National Security Emerging Technologies) and began working with big data in geographic research. Her work on the PlanetSense team utilized Python scripting to extract, clean, and update large amounts of Points of Interest (POI) data in an ElasticSearch cluster. She was in charge of building and managing a Neo4j graph database for POI category information which is now used daily for POI data enrichment. This sparked her interest in further pursuing data science, analytics, and data engineering at the big data scale, leading her to high-performance computing (HPC).
Rachel’s focus at ORNL will be contributing to the HPC Core Operations’ Analytics and Monitoring team to better understand, utilize, and visualize the large amount of HPC systems data in order to facilitate informed decision making.