Summary
George Watson-hyde is a Lead Machine Learning Scientist with a PhD in computational biophysics and a decade of experience applying ML, statistics, and simulation to scientific and public-sector problems. He builds data and ML capability from scratch in complex organisations, currently establishing an AI function for aptamer discovery in biotech. His background spans high-performance biomolecular simulation, interpretable deep learning, and production ML tooling—skills he used to architect model stores, semantic embeddings, and Bayesian algorithms at the UK Department for Work and Pensions. He combines hands-on technical delivery with people leadership, having line-managed and mentored data scientists while running large A/B testing and RCT programmes. He enjoys working at disciplinary interfaces, integrating wet-lab experiments with ML and simulation to accelerate R&D and commercial impact. Outside work he’s likely to be at a parkrun, reading, practising Greek, or losing time to Cities: Skylines videos.
10 years of coding experience
4 years of employment as a software developer
PhD, Physics, PhD, Physics at University of York
Greek, English