Eyal Kazin
Lead Data Scientist
London, England, United Kingdom
Summary
👤
Senior🎓
Top SchoolEyal 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 UniversityS2DSBachelor of Science (BSc.), Physics, Bachelor of Science (BSc.), Physics at Ben-Gurion University of the Negevביה״ס ניל״יMiddle School, Middle School at ORT CollegesHigh School Diploma, Electronics, High School Diploma, Electronics at קציני ים עכו
English, Hebrew, Spanish, Portuguese, French
Stackoverflow
1reputation
0reached
0answers
0questions
Github Skills (37)
probabilistic-graphical-models10
pytorch9
multi-objective-optimization9
python9
machine-learning9
deep-learning8
statistics8
data-science7
jupyter7
tensorflow7
bayesian7
data-analysis7
jupyter-notebook7
bayesian-inference6
neural-network6
Programming languages (5)
Github contributions (5)
elzurdo/elzurdo.github.io
Feb 2020 - Sep 2025
Sharing projects and ideas on my GitHub page
Contributions:20 PRs, 162 pushes, 25 branches in 5 years 8 months
javascriptreacttypescriptsharing
elzurdo/causal_inference
Jan 2021 - Nov 2024
Learnings in the field of Causal Inference
Contributions:4 PRs, 47 pushes, 6 branches in 3 years 10 months
causal-inference
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