Summary
Ewan Pinnington is a scientist and software engineer with 12 years’ experience applying machine learning, data assimilation and HPC to Earth system and climate problems. Currently at ECMWF, he develops next-generation reanalysis and ensemble prediction systems that assimilate novel satellite streams and propagate uncertainty with Bayesian ensemble methods. Previously a tech lead at Cervest, he scaled climate-intelligence services and led backend strategy to deliver global signals for hazards like runoff, landslides and heat stress. His PhD in Mathematics and Climate Science underpins a strong blend of theory and production engineering—he’s comfortable writing ML operators for HPC pipelines as well as pragmatic cloud-based data products. Notably, he has translated novel techniques (eg. LAVENDAR) from academic projects into funded operational workflows for drought, soil moisture and crop monitoring. Based in the Greater Reading area, he combines research credentials with hands-on systems delivery across big-data and scientific computing environments.
11 years of coding experience
6 years of employment as a software developer
Doctor of Philosophy - PhD, Mathematics and Climate Science, Doctor of Philosophy - PhD, Mathematics and Climate Science at University of Reading