Christopher Archer is a researcher and PhD candidate in Computer Science based in Berkeley with nine years of experience applying computational statistics and data engineering to data science and financial engineering problems. Trained in Operations Research at Cornell, he has combined academic research roles at top institutions with hands-on industry experience as a data engineer at Meta and internships at Microsoft, giving him fluency in turning statistical methods into production data systems. His background spans predictive modeling in biostatistics to applied research in materials and fluid interfaces, reflecting a knack for cross-disciplinary problem solving. At Berkeley he continues to bridge theory and practice, focusing on scalable statistical methods for real-world decision-making.
9 years of coding experience
5 years of employment as a software developer
Doctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at University of California, Berkeley
Bachelor of Applied Science - BASc, Operations Research, Bachelor of Applied Science - BASc, Operations Research at Cornell University
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Christopher Archer - Researcher at University of California, Berkeley