Summary
Charles Pehlivanian is a financial quant and quantitative modeler with over a decade of experience designing trading systems, pricing engines, and execution algorithms across US futures, equities and energy markets. He has led production implementations at global banks and fintechs—building FIX connectivity, feed handlers, and externalized risk/pricing platforms—and has hands-on expertise in C++, q/kdb, Python and Spark. At Goldman Sachs and Morgan Stanley he engineered high-frequency and agency trading strategies; more recently he scaled client-facing trade management systems at JPMorgan and directed market-facing infrastructure at Beacon Platform. Now based in New York, he combines academic rigor as an adjunct professor with ongoing senior development work at a boutique firm, bridging research-grade math (PhD in complex analysis) and production trading systems. Notably, he has implemented low-latency implied pricing servers for US energy markets and optimized TCA and strategy tooling for crude and products futures.
10 years of coding experience
21 years of employment as a software developer
PhD Mathematics : Complex Analysis, PhD Mathematics : Complex Analysis at University of Michigan
mandarin chineses, French