Summary
Alejandro Debus is a Staff Data Scientist and Machine Learning Engineer with a decade of experience building AI-driven products and leading teams across fintech, e-commerce, agtech, and edtech. He bridges data science, engineering, and product strategy to design, deploy, and scale production-grade search, recommendation, and MLOps platforms. His hands-on background spans deep learning, NLP, computer vision, reinforcement learning and cloud-native architectures, and he has shipped real-time anomaly detection, fraud models, and forecasting systems at Mercado Libre and Kueski. He also designs and teaches practical deep learning courses, translating complex research into usable lab exercises and production practices. Alejandro pairs an MBA and cloud data engineering training with a strong research footprint (Google Scholar) and open-source presence, bringing both business acumen and technical rigor to competitive intelligence and ML platform initiatives. Notably, he has applied photogrammetry and crop-analytics models in precision agriculture, reflecting a rare blend of applied research and product-focused delivery.
11 years of coding experience
5 years of employment as a software developer
Nivel Medio - Trayecto Técnico Profesional, Técnico en Informática Profesional y Personal, Nivel Medio - Trayecto Técnico Profesional, Técnico en Informática Profesional y Personal at Silose
Grado en Ingeniería, Ingeniería en Informática - Informatics Engineering, Grado en Ingeniería, Ingeniería en Informática - Informatics Engineering at Universidad Nacional del Litoral
Diplomatura en Cloud Data Engineering, Diplomatura en Cloud Data Engineering at Instituto Tecnológico de Buenos Aires
Master of Business Administration - MBA, Master of Business Administration - MBA at Collège de Paris
Nivel Medio - Polimodal, Economía y Gestión de las Organizaciones, Nivel Medio - Polimodal, Economía y Gestión de las Organizaciones at Colegio de Urdinarrain
Spanish, English