Raghav Somani is a quantitative researcher and analyst with 11 years of experience blending theoretical machine learning and optimization with practical equity portfolio construction. At D. E. Shaw he built medium- to long-term technical return forecasts and risk models that informed long-short equity strategies, drawing on a deep PhD-level background in high-dimensional statistics and algorithmic scaling. His research spans provable guarantees for large-scale iterative algorithms, streaming PCA, sparse regression, and applied probability—work developed at Microsoft Research and the University of Washington that translates directly into robust systematic signals. Comfortable moving between theory and production, he has a track record of turning geometric and statistical insights about financial time series into deployable forecasting tools. Based in New York and currently on gardening leave, he combines rigorous proofs-of-concept with pragmatic model engineering to improve portfolio pipelines. An under-the-radar strength is his ability to connect abstract optimization guarantees to practical model generalization in noisy, high-dimensional market data.
11 years of coding experience
7 years of employment as a software developer
Doctor of Philosophy - PhD, Computer Science and Engineering, Doctor of Philosophy - PhD, Computer Science and Engineering at University of Washington
Bachelor’s Degree, Mathematics and Computing, Bachelor’s Degree, Mathematics and Computing at Indian Institute of Technology, Guwahati
Higher Secondary, Science, Higher Secondary, Science at TECHNO INDIA, HOOGHLY 188
Secondary Education, General, Secondary Education, General at Hind Motor Education Centre
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Raghav Somani - Gardening Leave at The D. E. Shaw Group