Edgar Manrique is a Senior Data Scientist and PhD candidate in mathematical physics who combines ten years of experience with a strong record of applying machine learning to real-world problems, from fraud detection at Equifax to anomaly discovery in astronomical datasets. He leads open-source software for LEO satellite tracking and contributed a topological-data-analysis library for anomaly detection in light curves, blending research-grade methods with production-ready engineering. Edgar’s background as a physics instructor and mentor informs a pragmatic, explainable-ML approach and strong communication skills used to train students and cross-functional teams. At Equifax he helped develop a refund-fraud model projected to save a major merchant up to $1M by prioritizing the riskiest transactions. Fluent across Python, parallelized big-data workflows and interpretable ML, he is equally comfortable shipping models to production and teaching others to use them. He brings an unusual mix of astrophysics research, hands-on software leadership, and bilingual teaching experience rooted in Chile’s growing tech ecosystem.
10 years of coding experience
Certification, Data science and artificial intelligence, Certification, Data science and artificial intelligence at La Serena School for Data Science
Bachelor's degree, Physics, Licenciado en Física (Major in Physics), Bachelor's degree, Physics, Licenciado en Física (Major in Physics) at Universidad Central de Venezuela
Doctor of Philosophy - PhD, Anomaly detection, interpretable machine learning, astronomy and mathematical-physics, PhD - in progress, Doctor of Philosophy - PhD, Anomaly detection, interpretable machine learning, astronomy and mathematical-physics, PhD - in progress at Universidad de Antofagasta
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