Samuel Hansen is a data scientist and Stanford master's student in computational social science who leverages a decade of experience to optimize supply chains with the aim of improving millions of lives. Trained in neuroeconomics, symbolic systems, and Management Science & Engineering, he blends behavioral insight with rigorous quantitative methods to design practical, scalable optimization models. Based in San Francisco, Samuel focuses on translating academic research into real-world supply chain interventions and policy-relevant analyses. His background suggests a knack for interdisciplinary thinking—connecting human decision processes to algorithmic solutions—making him equally at home with stakeholder engagement and technical implementation.
10 years of coding experience
Bachelor of Science (BS), Neuroeconomics and Symbolic Systems, Bachelor of Science (BS), Neuroeconomics and Symbolic Systems at Stanford University
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