Eyal Kazin is a Lead Data Scientist based in London with 10+ years of experience turning complex scientific problems into practical, product-facing solutions. Trained as a cosmologist with a PhD from NYU, he blends rigorous statistical thinking and research-grade ML with hands-on engineering across healthcare, biotech, and marketing domains. He has built predictive models for protein design using multi-objective optimisation, improved clinical symptom-checker KPIs at Babylon, and led client-facing analytics that produced measurable business uplifts. Eyal is also a clear communicator and educator—publishing technical articles and translating findings for non-specialist stakeholders to drive decisions. He thrives on simplifying complexity into actionable insights and has a habit of bringing experimental design thinking from the lab into product teams.
10 years of coding experience
11 years of employment as a software developer
Doctor of Philosophy (PhD), Astronomy and Astrophysics, Doctor of Philosophy (PhD), Astronomy and Astrophysics at New York University
S2DS
Bachelor of Science (BSc.), Physics, Bachelor of Science (BSc.), Physics at Ben-Gurion University of the Negev
ביה״ס ניל״י
Middle School, Middle School at ORT Colleges
High School Diploma, Electronics, High School Diploma, Electronics at קציני ים עכו
Material for learning and practicing the technique of multi-objective optimisation
Contributions:113 commits, 10 PRs, 101 pushes in 9 months
practicingoptimizationmulti-objectivetechnique
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