Senior Data Scientist - Surge/Dynamic Pricing @ My team focuses on the mathematics and optimization of the execution of Uber's marketplace. That is, we focus on the operational issues of optimizing our real-time logistics platform via on-line dispatching optimization, optimal positioning of drivers in anticipation of demand patterns, the economic problem of how to dynamically price trips to optimize the efficiency of our marketplace, as well as many others. We are interested in hiring the top professionals & academics in the field of Economics, Econometrics, Finance, Quantitative Marketing, Statistics, Operations Research, and Industrial Engineering. Please reach out to me directly via LinkedIn if this matches your profile and are interested in opportunities with the team. --- I led the formation of Uber's Data Science Modeling Team, which develops the advanced mathematics and algorithms which enable new innovation and improved efficiency in the product. This is Uber's team of economists, statisticians, and operations researchers who develop and own the mathematical and computational technology which is used for optimizing our dynamic pricing process, optimizing the rider/driver dispatching system, forecasting systems, traffic pattern analysis/detection, and many more. This set of teams has now grown to around 15 scientists in less than a year. - Developed UberPool matching algorithms/mathematics - Col-led surge pricing mathematics & architectural development - Developed foundational mathematics for Uber's anomaly detection system - Sourced world-class talent for both junior and senior roles within the team - Leading Uber's real-time forecasting system development - Leading the forecasting and supply chain optimization efforts in the UberEATS food delivery product - Developing mathematical frameworks for Uber's real-time network optimization system which combines the joint optimization problems of dynamic pricing, matching optimization, open-car positioning, and driver incentives From April 2014 to Present (1 year 9 months) Fixed Income Quant Strat - Interest Rate Products @ From July 2013 to January 2014 (7 months) Consultant - Teaching Assistant/Instructor @ From March 2011 to September 2012 (1 year 7 months) Quant Portfolio Analyst @ From June 2009 to September 2010 (1 year 4 months) Summer Analyst @ From June 2007 to August 2007 (3 months) Summer Analyst @ From June 2006 to August 2006 (3 months) Midshipman 2/C @ From July 2003 to October 2005 (2 years 4 months)

PhD, Econometrics & Statistics @ University of Chicago From 2010 to 2013 MBA, Analytic Finance @ University of Chicago From 2009 to 2013 MS, Computer Science @ University of Chicago From 2008 to 2009 BSBA, Finance and Mathematics @ Washington University in St. Louis - Olin Business School From 2006 to 2008 BS, Aeronautical Engineering and Physics @ United States Naval Academy From 2003 to 2005 Howell High School Laszlo Korsos is skilled in: R, Matlab, Python, C++, Linux, C, Unix, Bloomberg, Java, Windows, Microsoft Excel, Mac OS, MPI, Eviews, Quantitative Finance