Saud Almahdi is a lead quantitative analytics specialist at Wells Fargo, where he develops models for the liquidity funding management team. He joined Wells Fargo in 2019 as a quantitative analytics specialist working on market and counterparty risk model development. In his current role, Saud designs and implements model backtesting programs and tools for monitoring, evaluation, and analysis. His professional interests center on machine learning model development for financial applications, with expertise in time series forecasting and analysis, predictive modeling, model monitoring and evaluation, portfolio optimization, and reinforcement learning.
Saud holds a BSc in control and instrumentation systems engineering from King Fahd University of Petroleum and Minerals. He earned an MSc and a PhD in financial engineering from Stevens Institute of Technology, where his research focused on reinforcement learning for dynamic portfolio optimization. He has authored and published several scholarly papers relevant to reinforcement learning, sentiment analysis, and the intersections of applied analytics and finance.
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