Summary
Gilberto Batres-Estrada is a Senior Data Scientist in Stockholm with eight years of experience applying deep learning, machine learning and quantitative methods to finance, telecom, logistics and security sectors. Trained as a physicist and applied mathematician (MSc Stockholm University; MSc KTH), he combines theoretical rigor with practical engineering to deliver production-ready ML and generative AI solutions as a consultant. He has deep hands-on experience with time series, LSTM networks, recommender systems, gradient boosting and big data pipelines, and has translated that work into teaching roles and a coauthored book chapter on LSTMs for stock prediction. As a frequent instructor and conference speaker, he distills complex models into actionable code for industry practitioners, particularly in financial applications. Notably, he blends research-level grounding in theory with long experience implementing efficient algorithms across diverse production environments.
8 years of coding experience
13 years of employment as a software developer
Summer school of deep learning, Artificial Intelligence, Summer school of deep learning, Artificial Intelligence at University of Deusto
Master of Science (MSc), Engineering Physics: Applied Mathematics and Statistics, Master of Science (MSc), Engineering Physics: Applied Mathematics and Statistics at KTH Royal Institute of Technology
Summer school on Deep Learning, Deep Learning and Artificial Intelligence, Summer school on Deep Learning, Deep Learning and Artificial Intelligence at Università degli Studi di Genova
Master of Science (MSc), Theoretical and Mathematical Physics, Master of Science (MSc), Theoretical and Mathematical Physics at Stockholm University
Spanish, Swedish, English, French