Guner Celik

Head of US Treasury Algorithmic Quantitative Research and Business Development Cantor Fitzgerald

Guner Celik is Head of US Treasury Algorithmic Quantitative Research and Business Development at Cantor Fitzgerald. Guner joined the Cantor from Springtech Capital where he was a co-founder and led research and algorithmic trading efforts. Prior to Springtech, Guner worked as a VP of Algorithmic Trading and Quantitative Research at Goldman Sachs for systematic market making in fixed income and commodities; and prior to Goldman, he was a Senior Mathematical Modeling and Algorithms Specialist and Software Developer at Oracle. He has extensive experience developing algorithms for electronic trading, market making, signal generation, RFQ systems, and a strong background in probability theory, optimization, algorithms, and machine learning. Guner holds both a PhD and M.S. in Electrical Engineering and Computer Science from MIT summa cum laude and he has a B.Sc. in Electrical Engineering from METU, where he was ranked 2nd in the engineering department.