Summary
Andres Babino is a data scientist with 11 years of experience who blends academic rigor from a PhD in Physics with hands-on ML and engineering practice to tackle complex real-world problems. He has applied deep learning, causal inference, and experimental methods across domains—from building underwater audio/image pipelines to improve dolphin behavior research to optimizing product features at ASAPP and now illuminating the MEV “dark forest” at Flashbots. Andres is a full-stack practitioner who moves seamlessly between research-quality reproducible code (Fastpapers, nbdev notebooks) and production systems (Django, Celery, NGINX), and he has a track record of publishing and open-sourcing tools used by the community. Notably, he converts hardware constraints into data pipelines—modifying cameras and designing hydrophone arrays—and translates that interdisciplinary work into deployable ML systems.
11 years of coding experience
6 years of employment as a software developer
Doctor of Philosophy - PhD, Physics, Doctor of Philosophy - PhD, Physics at University of Buenos Aires