Tyler Richardett is a data science and engineering leader with eight years of experience building production ML and computer vision systems, now serving as CTO in Washington, D.C. He has led cross-functional teams to deploy large-scale solutions—such as a document-tagging pipeline processing 200,000 items per day and facial-photo validation models—bridging research-grade methods with operational impact in government and enterprise settings. Comfortable in R and growing his Python skillset, Tyler blends unsupervised learning, optimization, and geospatial analysis with practical ML engineering at companies from Databricks to SAIC. His early career in data storytelling and award-winning visualization work informs a talent for translating complex policy and behavioral datasets into actionable products. Outside work he applies the same data-first mindset to youth and professional soccer, collecting event-level play data to surface insights on access and mobility.
9 years of coding experience
8 years of employment as a software developer
Bachelor of Arts - BA Public Relations & Strategic Communication, Bachelor of Arts - BA Public Relations & Strategic Communication at American University
Master of Science - MS Data Analytics Engineering, Master of Science - MS Data Analytics Engineering at George Mason University
American Soccer Analysis interactive application, built with Shiny.
Contributions:3 releases, 12 reviews, 296 commits in 3 years
shinysocceramericaninteractive-analysisr
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