Daniel Domingo-fernández is a data science leader with a decade of experience at the intersection of machine learning and biomedicine, currently serving as VP, Data Science at Enveda while managing a remote, intercontinental team. He combines deep domain expertise in drug discovery, cheminformatics, metabolomics and experimental biology with a strong academic foundation (MS and PhD in Life Science Informatics from the University of Bonn). His career spans applied research at Fraunhofer and teaching roles at the University of Bonn, where he supervised students and translated patient-level and mass-spectrometry data into actionable biomedical insights. Known for bridging rigorous research and product-driven teams, he has repeatedly advanced mechanism-enrichment and knowledge-graph approaches in translational projects. Colleagues rely on him for translating complex biological problems into deployable ML solutions that accelerate drug discovery.
9 years of coding experience
8 years of employment as a software developer
Exchange Student Bachelor of Science (BSc) in Biotechnology, Biotechnology, Exchange Student Bachelor of Science (BSc) in Biotechnology, Biotechnology at University of Wisconsin-Green Bay
Bachelor of Science (BSc) in Biotechnology, Biotechnology, Bachelor of Science (BSc) in Biotechnology, Biotechnology at Universidad de León
Doctor of Philosophy - PhD, Biomathematics, Bioinformatics, and Computational Biology, Doctor of Philosophy - PhD, Biomathematics, Bioinformatics, and Computational Biology at The University of Bonn
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