Summary
Pablo Viana is a Lead Data Scientist with a decade of experience building production-ready AI systems in high-stakes financial environments, combining applied mathematics and economics with an MSc in Artificial Intelligence. He specializes in GenAI, retrieval-augmented systems, recommendation and ranking engines, and self-supervised representation learning, having led cross-functional teams at BBVA AI Factory to deploy solutions that read scanned documents, navigate massive data lakes, and detect messaging inconsistencies with explainability in mind. Pablo thrives at the R&D–productization boundary, turning embedding spaces and LLMs into measurable business value and operational tools used by stakeholders. He pairs rigorous experimentation (contextual bandits, uplift modeling interest) with practical engineering—Docker, LangChain, Qdrant, OpenSearch and production pipelines—ensuring models work beyond the lab. Based in Madrid, he’s open to roles in internet, e-commerce, retail, travel or finance where personalization, causal inference, or uplift modeling are needed.
10 years of coding experience
5 years of employment as a software developer
Master of Science Artificial Intelligence, Master of Science Artificial Intelligence at The University of Edinburgh
Bachelor of Arts - BA Economics, Bachelor of Arts - BA Economics at Instituto Tecnológico Autónomo de México