Summary
Kaido Lepik is a Senior Data Engineer with nine years of experience bridging statistical genetics research and production-grade data systems. He holds a PhD in Computer Science and has translated deep methodological expertise from postdoctoral work in causal mediation into scalable, reproducible pipelines used in both academia and industry. At Geneto he led R&D and built an automated genetics-based disease prediction workflow that achieved CE certification, and he currently applies similar rigor at Microsoft while maintaining active research at the University of Lausanne. Kaido combines advanced probabilistic modeling and causal inference with practical engineering—building end-to-end solutions that integrate omics, EHRs, and large-scale analytics. Known for diving deep into narrow technical challenges, he also has a track record of fostering cross-institutional collaborations across Estonia, the Netherlands and Switzerland. Based in Tartu, he balances research curiosity with product-minded delivery, turning complex genetic insights into auditable, production systems.
8 years of coding experience
7 years of employment as a software developer
High School, Mathematics, High School, Mathematics at Hugo Treffneri Gümnaasium
Doctor of Philosophy (PhD), Computer Science, Doctor of Philosophy (PhD), Computer Science at University of Tartu
Master's Degree, Mathematical Statistics, cum laude (5.0/5.0), Master's Degree, Mathematical Statistics, cum laude (5.0/5.0) at Tartu Ülikool
Estonian, English, French