Prakhar Bansal is a low-latency C++ software developer with nine years of experience building high-performance trading and quantitative systems across firms like Nomura, Daksh Trading, and Belvedere Trading. He blends a strong academic background from IIT Delhi and an MS in Quantitative Finance from Washington University with hands-on experience in market-facing and research roles, including developing an LLM tailored to reduce lookahead bias in financial data. His work spans ultra-low-latency C++ engineering, quantitative modeling, and bespoke tooling—evidenced by research projects from photon-counting instrumentation to terahertz sensor modeling. Comfortable moving between research and production, he has a track record of shipping robust, performance-critical code in trading environments. Colleagues would note his knack for translating complex stochastic models into efficient implementations and his habit of explaining tricky concepts succinctly—hence the apt GitHub quip, "dp explains it lol."
9 years of coding experience
5 years of employment as a software developer
Indian Institute of Technology Delhi (IIT Delhi)
Master of Science - MS Quantitative Finance, Master of Science - MS Quantitative Finance at Washington University in St. Louis
Contributions:7 pushes, 1 branch in 1 year 5 months
learning-codespythonmachine-learningdata-science
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