Summary
Dan Smith is a data scientist with 14 years of experience building human-first knowledge discovery workflows that turn vast structured and unstructured biomedical data into actionable hypotheses. Currently at GSK after leading data science at BenevolentAI, he has a track record of shipping production Python packages, web APIs, and interactive visual tools that bridge researchers and models. His work spans literature mining, knowledge graph traversal, LLM tuning, agent-style prompt engineering and pattern mining to support high-stakes decision making and drug repurposing efforts. Notably, he led the technical approach that contributed to identifying baricitinib for COVID-19 and has driven partnerships that achieved in vitro and in vivo successes. He pairs deep technical craftsmanship—GLSL/WebGL visualizations, Streamlit apps, Airflow ETLs and graph analytics—with product and UX leadership to make complex AI outputs interpretable for domain experts. Based in London, he focuses on human–machine collaboration to accelerate scientific discovery.
14 years of coding experience
14 years of employment as a software developer
Camden School for Girls, London
Highgate School, London
BSc (Hons.) Multimedia Computing with Industrial Experience, BSc (Hons.) Multimedia Computing with Industrial Experience at Queen Mary University of London
University College London