Jason Bixon is a data analyst in Baltimore with eight years of experience building analytical and predictive solutions for healthcare and nonprofit clients. He combines statistical modeling, NLP, geospatial analysis, and interactive visualization to translate disparate data feeds into actionable insights and operational tools. Prior roles span hospitals, agencies, and civic tech—where he contributed to Code for Baltimore projects that improved service delivery and emergency response. His background as a psychology research PI informs rigorous experimental design, IRB processes, and survey methodology that strengthen causal claims in his analyses. Jason also contributes to open-source front-end tooling for react-three-fiber, having improved the usability of the popular drei Sky component by simplifying sun-position properties into a single prop. He is adept at shipping end-to-end analytical products using SQL, BigQuery, R, SAS, and Tableau/R Shiny for measurable program and fundraising impact.
8 years of coding experience
3 years of employment as a software developer
Bachelor of Science (B.S.), Marketing, Bachelor of Science (B.S.), Marketing at Penn State University
Contributions:6 reviews, 8 commits, 3 PRs in 4 months
Contributions summary:Jason primarily focused on enhancing the `Sky` component within the `drei` library, which provides useful helpers for React-Three-Fiber. They refactored the sun positioning logic within the Sky component and its corresponding storybook stories. The user made several changes to the component's properties, including the introduction of inclination and azimuth, and then consolidated these properties into a single `sunPosition` prop. These changes improved the component's functionality and usability within the React-Three-Fiber environment.
Contributions:44 commits, 52 pushes, 1 branch in 9 months
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