Principal Machine Learning Engineer at Local Parish Councillors
Cambridge, England, United Kingdom
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Summary
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Daniel O'donovan is a Principal Machine Learning Engineer with 16 years of experience applying graph-based ML and large-scale data integration to accelerate rare disease drug discovery. At Healx he has designed and deployed production ML systems that prioritize therapeutic candidates and translate model outputs into actionable research and clinical decisions. His background spans biochemistry (PhD), high-performance computing, and practical software engineering, enabling him to bridge technical, biological, and regulatory perspectives. He leads cross-functional teams on knowledge-graph reasoning, interpretability, and responsible AI in healthcare, and has a track record of embedding reproducible ML practices across organisations. Outside work he co-founded an IoT agri-tech startup and serves as a trustee handling charity governance and finance, reflecting a mix of entrepreneurial drive and community stewardship.
16 years of coding experience
10 years of employment as a software developer
Doctor of Philosophy (Ph.D.), Biochemistry, Doctor of Philosophy (Ph.D.), Biochemistry at University of Cambridge
Master of Science (M.Sc.), High Performance Computing, Master of Science (M.Sc.), High Performance Computing at Trinity College Dublin
Bachelor of Science (B.Sc.), Physics and Mathematics, Bachelor of Science (B.Sc.), Physics and Mathematics at University of Warwick
Contributions:238 commits, 44 PRs, 89 pushes in 8 years 5 months
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