Ramchandra Apte is a quantitative developer-researcher with 11 years of experience building high-performance trading systems and analytics across both traditional and crypto markets. He has shipped production C++ trading engines and backend services in Rust, contributed to zero-knowledge-powered crypto exchange features, and improved price valuation and execution tools at high-frequency firms. His work spans research into US equity microstructure, generative-AI tooling for structured finance, and practical backtesting and benchmarking using Pandas and Jupyter. A former IOI 2018 and ICPC North American finalist, he combines deep algorithmic skills with hands-on software engineering to bridge research and production. Based in Bengaluru with a global career footprint, he’s comfortable optimizing low-latency systems and building ML-augmented tooling for domain specialists. An under-the-radar strength is translating complex quantitative models into robust APIs and observability improvements that directly move P&L.
11 years of coding experience
3 years of employment as a software developer
Bachelor's degree Computer Science, Bachelor's degree Computer Science at University of Michigan
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