Jacob Bowers Blackrock Quant Lead

QuantVision 2026: Fordham’s Quantitative Conference
Jacob Bowers is a Vice President in Quantitative Research and Financial Engineering at BlackRock, based in the San Francisco Bay Area. He leads initiatives across multi asset portfolio construction, performance monitoring and attribution, liquidity aware portfolio optimization, and the modeling of market impact and transaction costs for very large block trades. His work sits at the intersection of portfolio theory, large scale implementation, and real world trading constraints.

Previously, Jacob served as a Senior Associate supporting BlackRock’s Retirement Solutions business, where he acted as lead quantitative developer for portfolios exceeding five hundred billion dollars in assets. He led the Real Asset Change two point zero model upgrade, integrating CPI data and inflation robust portfolio engineering into the LifePath framework, with deployment across twelve client portfolios totaling three hundred fifty billion dollars. He also engineered the asset allocation model behind the LifePath ETF launch and partnered directly with portfolio managers on LifePath Paycheck, a thirty billion dollar product. He received a top tier performance rating for this work. Earlier roles at BlackRock included multi asset model engineering and software development within the Aladdin Wealth Enterprise platform.
Before BlackRock, Jacob held research and engineering roles at National Renewable Energy Laboratory, Sandia National Laboratories, and MIT Lincoln Laboratory, with work spanning bioinformatics, seismic signal processing for nuclear monitoring, and cyber analytics using graph based intrusion detection. His academic background includes an MS in Computer Science and a BS in Mathematics and Computer Science from Florida Institute of Technology, where he graduated magna cum laude with a near perfect academic record and extensive research experience in stochastic processes, neural networks, and multi agent systems.
QuantVision 2026: Fordham’s Quantitative Conference



