Zijun Yi is a Data Engineer with nine years of hands-on experience building production-ready ML systems, currently optimizing predictive model backends and CI/CD on Azure and Kubernetes at NielsenIQ. With an M.S. in Applied Data Science from Syracuse University and a background bridging research and front-end development, Zijun translates complex algorithms into scalable, customer-focused solutions. Known for improving system performance (e.g., a 40% optimization in production) and managing reliable delivery pipelines, he operates effectively between scientists and end-users. Outside work he tinkers with mechanical keyboards and hones his focus with competitive ping pong, reflecting a detail-oriented, performance-driven mindset.
9 years of coding experience
2 years of employment as a software developer
M.S. degree, Applied Data Science, M.S. degree, Applied Data Science at Syracuse University
Science of Science Summer School (S4) 2021 website
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