Summary
Edinson Medina is a Senior Data Scientist based in New York with over seven years of experience applying machine learning and quantitative methods across finance, energy, and advisory roles. He has built high-return trading strategies and automated anomaly detection for equities, led reservoir characterization projects that de-risked multimillion-dollar drilling investments, and improved fluid distribution predictions by 20% using supervised models. As an instructor he has taught 200+ students, maintained an 85%+ attendance rate, and evaluated 150+ capstone projects, translating complex concepts into hands-on, industry-relevant learning. Comfortable with end-to-end solutions—from seismic data processing and Fortran tools to Python-based ML pipelines—he blends domain expertise in geophysics with practical data science to drive measurable business outcomes. Notably, his work has repeatedly turned large, noisy scientific datasets into actionable models that both reduce operational costs and generate significant returns.
6 years of coding experience
10 years of employment as a software developer
Master's degree in Earth Sciences, Geosciences Applied to Petroleum, Master's degree in Earth Sciences, Geosciences Applied to Petroleum at Universidad Simón Bolívar
Spanish, English, French