Clayton Thorrez is a data scientist and applied ML researcher with nine years of experience building applied NLP and LLM tooling at Microsoft, Apple, and startups; he now works as a Member of the Technical Staff focused on leaderboard and ranking systems at Arena. He specializes in paired comparison and rating-system methods for preference modeling, model evaluation, and post-training calibration, and brings that expertise to both production ML products and niche analyses of esports competitions. Clayton’s work spans evaluation pipelines for LLMs and applied ML in collaboration features like Outlook and Teams, and he has published practical datasets and demos such as EsportsBench and the Riix project. Comfortable moving between research and engineering, he blends statistical rigor with production mindset—often using competitive-sports data as a creative testbed for rating algorithms.
9 years of coding experience
8 years of employment as a software developer
Hillsdale Academy
Bachelor of Science in Engineering (BSE) Computer Science Data Science, Bachelor of Science in Engineering (BSE) Computer Science Data Science at University of Michigan College of Engineering
Master's of Science Computer Science, Master's of Science Computer Science at University of Massachusetts Amherst
Contributions:11 commits, 9 pushes, 1 branch in 10 months
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Clayton Thorrez - Member Of The Technical Staff at Arena