ÂÜÀòÂÒÂ×

Nicholas Amirsoleimani is a Junior Quantitative Researcher at Arbol, with prior experience as a Statistics and Optimization Intern at NASA, where development within the UTM ecosystem was orchestrated using advanced linear programming and a novel technique was developed to address model infeasibilities. A former Design Engineer at Western Allied Mechanical, Nicholas executed mechanical design calculations and collaborated on HVAC equipment layouts. As a Financial Machine Learning and Statistics Intern at PredictNow.ai Inc, Nicholas integrated modern methodologies in Python for mean-reverting portfolios. Additional roles include tutoring at the University of California, Davis, and conducting quantitative analyses at MAJERKO INVESTMENT MANAGEMENT INC. Nicholas holds a Master of Arts in Statistics from the University of California, Berkeley, and dual Bachelor of Science degrees in Aerospace Science and Engineering and Mechanical Engineering from the University of California, Davis.