Summary
Chinny Emeka is a researcher and data scientist with 11 years of experience blending software engineering, machine learning, and mixed-methods research to solve real-world problems. Based at the University of Illinois Urbana-Champaign, he combines PhD-level research with hands-on engineering—building data pipelines, causal modeling tools, and web applications for production use. His internships at CME Group and Whole Tale demonstrate practical expertise in Python, R, Java, and database migrations, plus a focus on data integrity and bias mitigation. As a former outstanding graduate teaching assistant, he also brings clear communication and pedagogy to complex technical topics. Chinny’s work often sits at the intersection of NLP, causal inference, and systems engineering, enabling reproducible, analyzable workflows for research and industry. He’s equally comfortable prototyping algorithms and hardening them into maintainable software for analytics-driven teams.
10 years of coding experience
3 years of employment as a software developer
University of Illinois Urbana-Champaign
Bachelor’s Degree, Computer Science, Bachelor’s Degree, Computer Science at Valparaiso University
English, French