Summary
Daniel Viejo is a Senior Data Scientist and Generative AI engineer with six years of experience building production-grade RAG systems, chatbots, and analytics platforms across Azure and AWS for clients including AstraZeneca, Repsol and the Spanish Ministry of Digital Transformation. He blends strong mathematical grounding (MSc in AI, BScs in Data Analytics and Mathematical Sciences) with hands-on expertise in fine-tuning, LLM orchestration, graph-augmented retrieval, and scalable MLOps, backed by multiple Microsoft, AWS and GCP certifications. At AstraZeneca he led a global analytics platform used by 1,500+ stakeholders and prototyped a GraphRAG PoC that balances hybrid retrieval latency and accuracy. A practical teacher and mentor, he has developed generative AI curricula for universities and industry, and his background in business analytics helps him translate complex models into measurable customer and societal impact. Notably, he combines a production-first mindset with research-level rigor—his MSc thesis implemented and evaluated RAG for legal queries, a thread that recurs across his commercial work.
6 years of coding experience
1 year of employment as a software developer
Bachelor of Science (BS) in Business Data Analytics (1º Promotion) Business Artificial Intelligence and Programming, Bachelor of Science (BS) in Business Data Analytics (1º Promotion) Business Artificial Intelligence and Programming at Mondragon Unibertsitatea
Mathematical Sciences Mathematics and Computer science, Mathematical Sciences Mathematics and Computer science at University of Essex
Master of Science (MSc) in Artificial Intelligence Computer Science, Master of Science (MSc) in Artificial Intelligence Computer Science at Universidad Internacional de La Rioja
High School Diploma Technology, High School Diploma Technology at Maristak Bilbao
English, Basque, Spanish