Daniel Morgan is a Data Scientist with 11 years of experience who blends graph theory, algorithm development, and data visualization to solve complex biological problems. Currently at Olink Proteomics in Stockholm, he applies his PhD-trained analytical rigor from Stockholm University to extract actionable insights from proteomics and biochemical data. Known as a "graph nerd" and self-described hacker of the bio-mainframe, he builds bespoke graph-based models and visual tools that make high-dimensional biology more interpretable. His background includes a master’s from The Ohio State University and a track record of turning research-grade methods into production-ready analyses. Colleagues value his mix of deep domain knowledge and practical engineering chops, particularly in algorithm design for messy experimental datasets. He often surfaces non-obvious relationships in data by combining network perspectives with elegant visual narratives.
11 years of coding experience
Master's degree, Master's degree at The Ohio State University
Doctor of Philosophy (Ph.D.), Doctor of Philosophy (Ph.D.) at Stockholm University
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