Christopher Llop is a data-driven technology leader with 11 years of experience guiding technical and data science teams in complex litigation, regulatory, and energy economics engagements. As Vice President at Analysis Group, he combines hands-on code analysis, statistical modeling, and reverse-engineering of production systems to produce defensible expert work in IP, antitrust, and financial disputes. He teaches Python fundamentals at UC Berkeley’s MIDS program, translating real-world casework into practical coursework consistently rated among the program’s best. His background in electrical engineering and early engineering internships informs a meticulous, systems-oriented approach to data pipelines and reproducible analyses. Known for building “Code Rooms,” automated review scripts, and interactive economic models, he brings a rare blend of academic rigor, courtroom-ready forensics, and operational tooling to multidisciplinary teams.
11 years of coding experience
11 years of employment as a software developer
Masters of Information and Data Science (MIDS), 3.84, Masters of Information and Data Science (MIDS), 3.84 at UC Berkeley School of Information
Language Study, Intermediate Level Mandarin, Language Study, Intermediate Level Mandarin at Capital Normal University
Bachelor of Science, Electrical Engineering, 3.68, Bachelor of Science, Electrical Engineering, 3.68 at State University of New York at Buffalo
Selected Classes, Statistics and Microeconomics, 4.0, Selected Classes, Statistics and Microeconomics, 4.0 at Harvard Extension School
Contributions:3 PRs, 20 pushes, 1 comment in 1 month
deep-learningpythonmachine-learningdata-science
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