Summary
Rachel Keay is a Senior Data Scientist with nine years' experience applying machine learning to marine and geospatial problems, currently leading data science delivery at the UK Hydrographic Office. She combines deep technical skills in computer vision, deep learning, NLP and satellite-derived analytics with hands-on productionisation on AWS, GCP and Google Earth Engine to move models from research to operational services. Her work spans automatic target recognition in side-scan sonar, satellite-derived bathymetry that meets IHO S-67 standards, tidal time-series analysis, and habitat classification for seagrass, kelp and mangroves. A strong Agile collaborator and project leader, she translates business priorities into reproducible, testable datasets and evaluation pipelines. Notably, she has productionised a tidal contours coastline algorithm and applied blob-detection on Sentinel-1 SAR to enhance maritime situational awareness—demonstrating a rare blend of domain expertise in hydrography and practical ML engineering.
9 years of coding experience
11 years of employment as a software developer
Master's Degree Geographic Information Systems, Master's Degree Geographic Information Systems at University of Aberdeen
High School Highers and Advanced Higher, High School Highers and Advanced Higher at Belmont Academy
Master of Science - MS Data Science, Master of Science - MS Data Science at University of Exeter
Bachelor's Degree Geography, Bachelor's Degree Geography at University of Glasgow