Summary
Michael Gurkov is a data scientist at the Bank of Israel with eight years of experience bridging quantitative economic research and applied machine learning. He designs and deploys LLM-based pipelines for aspect-based sentiment analysis and Retrieval-Augmented Generation to make database queries more natural and actionable for policy teams. His work on anomaly detection targets abnormal market activity, helping safeguard the integrity of economic data used for regulation and analysis. Michael also maintains a long-standing academic footprint as a lecturer and former research fellow, translating complex methods into teachable material across several Israeli institutions. Trained in financial economics (M.A., The Hebrew University) with a BA in Economics and Management, he blends rigorous economic theory with practical ML engineering. Less obvious: he routinely moves between research, teaching, and production work, giving him rare fluency in communicating technical results to both academic and regulatory audiences.
8 years of coding experience
Bachelor of Arts (BA), Economics and Management, 94, Bachelor of Arts (BA), Economics and Management, 94 at The Academic College of Tel-Aviv, Yaffo
Master of Arts (M.A.), Financial Economics, 93, Master of Arts (M.A.), Financial Economics, 93 at The Hebrew University
English, Hebrew, Russian