Summary
Alvaro Cordon is a data scientist and team leader with a PhD in physics and over a decade of experience turning messy, large-scale data into business impact across industries from rail engineering to finance. He blends theoretical rigor in mathematical modelling with hands-on expertise in Python, Spark, TensorFlow/PyTorch and HPC (CUDA/RAPIDS), routinely taking projects from proposal through deployment using Docker, MLflow and REST APIs. His work spans predictive maintenance, NLP with transformers, recommender systems and financial analytics, and he has led cross-functional teams to deliver productionized solutions for clients like BBVA and CAF. An active academic with 20+ peer-reviewed publications and teaching roles at IE, UGR and UMA, he uniquely bridges cutting-edge research and pragmatic product delivery. Based in Málaga, he also consults on AI strategy (Quant AI Lab) and maintains an applied open-source presence on GitHub, reflecting a rare mix of deep theory, large-scale engineering and stakeholder-facing communication.
11 years of coding experience
11 years of employment as a software developer
Doctor of Philosophy (Ph.D.) Physics, Doctor of Philosophy (Ph.D.) Physics at Universidad de Granada
Master’s Degree Financial Engineering, Master’s Degree Financial Engineering at WorldQuant University
Master's degree Statistical Learning & Data Mining, Master's degree Statistical Learning & Data Mining at Universidad Nacional de Educación a Distancia - U.N.E.D.