Summary
Miguel Alvarez is a Head of Data Science and mathematician specialized in Operations Research, with nearly a decade of hands-on experience building optimization and machine learning solutions for complex, data-driven decision problems. He progressed from optimization consultant roles to leading data science teams at CARTO and Glovo, combining product-focused leadership with technical delivery in geospatial and logistics contexts. As an adjunct professor at two Spanish universities, he translates research-grade methods into teachable, practical workflows for students and practitioners. His background includes an MIT MicroMasters in Supply Chain Management and international studies across Amsterdam and Chicago, reflecting a global, systems-oriented approach to problems. Known for turning mathematical models into production-ready tools, he excels at aligning algorithmic rigor with business impact. Based in Greater Madrid, he brings a rare blend of academic depth and operational experience in routing, resource allocation, and spatial analytics.
9 years of coding experience
15 years of employment as a software developer
MicroMasters Program in Supply Chain Management, MicroMasters Program in Supply Chain Management at Massachusetts Institute of Technology
International Relations, International Relations at Loyola University Chicago
Licenciatura en Matemáticas Mathematics, Licenciatura en Matemáticas Mathematics at Universidad Complutense de Madrid
Mathematics, Mathematics at University of Amsterdam
Spanish, English, neerlandés