Alfredo Olguin
University Lecturer at Infotec, Centro de Investigación e Innovación en TIC
Mexico City
Summary
👤
Senior🎓
Top SchoolAlfredo Olguin is a data scientist and university lecturer with 11 years of experience applying causal inference, time series forecasting, and classification to drive measurable marketing impact across global teams at KAYAK and Uber. He blends academic rigor—Harvard and Johns Hopkins training and published research in text mining—with hands-on production work such as Marketing Mix Modeling, geo/causal experimentation, churn prediction, and user-level credit scoring. Based in Mexico City, he has transitioned from industry problems to teaching and research roles at UNAM and Infotec while still delivering practical, revenue-driving models. Unusually for a practitioner, he pairs Bayesian methods and spatial clustering with neural networks, making research-grade techniques accessible to business stakeholders.
11 years of coding experience
9 years of employment as a software developer
Universidad Nacional Autónoma de México (UNAM)Master of Liberal Arts Management, Master of Liberal Arts Management at Harvard UniversityDouble Data Science Specialization Data Science, Double Data Science Specialization Data Science at Johns Hopkins Bloomberg School of Public HealthGraduate Research Internship in Text Mining Applied Mathematics, Graduate Research Internship in Text Mining Applied Mathematics at Centro de Ciencias de la Complejidad (C3)
Portuguese, Japanese, English, Spanish
Github Skills (7)
r-package5
twitter-client4
twitter3
network-analysis2
igraph2
network-visualization2
social-network-analysis2
Programming languages (1)
Github contributions (5)
alfredo203/economia_inteligencia_artificial
Dec 2016 - Apr 2018
Contributions:38 commits, 33 pushes, 1 branch in 1 year 3 months
alfredo203/programacion_lineal
Oct 2017 - Dec 2017
Contributions:16 pushes, 1 branch in 2 months
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