Lex O'brien is a data scientist and computational chemist with over a decade of experience applying scientific modelling, ML and optimisation to drug discovery, energy planning and large-scale chemical simulation. He has partnered with governments, the World Bank, academia and startups to deliver production-ready tools—from a full-stack, human-in-the-loop biochemical extraction system to least-cost energy expansion models. His recent roles span molecular dynamics and property-prediction ML for lead optimisation, as well as research into online deep learning for molecular kinetics. Comfortable across research and software engineering, he builds CI/CD pipelines, leverages GCP compute, and collaborates via GitHub to move models into production. Based in Glasgow, he combines a PhD in Chemistry with hands-on experience in experimental dataset generation and systematic chemical-space exploration. A less obvious strength is his ability to translate complex academic methods into scalable engineering workflows that deliver actionable insights for both scientific and policy stakeholders.
11 years of coding experience
5 years of employment as a software developer
Master of Chemistry - MChem, Chemistry, Master of Chemistry - MChem, Chemistry at University of Oxford
Master of Science - MS, Engineering Physics/Applied Physics, Master of Science - MS, Engineering Physics/Applied Physics at Harvard University
Doctor of Philosophy - PhD, Chemistry, Doctor of Philosophy - PhD, Chemistry at University of Bristol
Contributions:25 pushes, 2 branches in 6 years 7 months
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