Nathan Sanglier is an experienced intern and emerging quantitative analyst with a strong academic background. Nathan has completed internships at UCLouvain's LIDAM/LFIN as a Quant Research Intern, focusing on quantitative finance research, and at EY in the Quantitative Advisory Services team, working on deep learning techniques and Monte Carlo methods for financial analysis. Previously, Nathan gained experience as a Software Engineer Intern at Crédit Agricole Technologies et Services, where data pipelines for financial analysis were developed. Educational credentials include an engineering degree from IMT Atlantique, a semester at The London School of Economics and Political Science, and coursework at various prestigious institutions. Currently, Nathan is pursuing an M2MO degree at Univ Paris Diderot.
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