Scott Clark is a founder and engineering leader with 15 years of experience building and scaling AI-driven products, most notably co-founding SigOpt and guiding its acquisition by Intel to continue developing an Intelligent Experimentation platform. He blends deep academic expertise—a PhD in Applied Mathematics and MS in Computer Science from Cornell—with hands-on production experience applying optimal learning and Bayesian optimization across domains from bioinformatics to ad targeting. At Intel he led SigOpt post-acquisition and broader AI/HPC application enablement, and today he’s co-founder and CEO of Distributional, focusing on tooling to test and harden AI systems. His background includes building open-source optimization tooling at Yelp (MOE) and leading cross-disciplinary teams that translate advanced algorithms into measurable business impact. He serves on multiple advisory boards and local institutions, reflecting a commitment to both industry innovation and community engagement. An uncommon thread through his career is pairing theoretical optimal-learning research with pragmatic productization at scale.
15 years of coding experience
13 years of employment as a software developer
W15 Batch, W15 Batch at Y Combinator
BS (x3) BS Mathematics BS Physics BS Computational Physics, BS (x3) BS Mathematics BS Physics BS Computational Physics at Oregon State University
PhD Applied Math (ML and Optimization focus) M.S. in Computer Science, PhD Applied Math (ML and Optimization focus) M.S. in Computer Science at Cornell University
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