Michael Dyer

Staff Machine Learning Engineer at Snapdocs

Michael Dyer is an experienced Staff Machine Learning Engineer at Snapdocs, overseeing various Data Science services and contributing to company-wide architecture as a member of the Tech Council. Michael's expertise includes developing innovative machine learning products, such as a Signature Detection tool that generates significant revenue. Previous roles span across numerous companies, including Boulder AI, Pearson, and Orderly Health, where Michael implemented cutting-edge solutions in machine learning, real-time data visualization, and model optimization. Education includes a Bachelor’s Degree in Neuroscience from Hamilton College and further studies at the University of Pennsylvania and Galvanize Inc.

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Denver, United States

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Snapdocs

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Snapdocs powers homeownership. Using technology, thet’re building the connective tissue for an entire pillar of the U.S. economy: residential real estate.