Sukhdeep Singh
Quantitative Researcher
Menlo Park, California, United States
Summary
👤
Senior🎓
Top SchoolSukhdeep Singh is a quantitative researcher at Goldman Sachs with 11 years of experience bringing rigorous statistical and ML validation to high-stakes finance and scientific problems. He transitioned from a distinguished academic career at CMU and Berkeley—where he authored 30+ papers with 1,000+ citations and built GPU-accelerated, distributed pipelines—to owning the validation lifecycle for 100+ models across Asset & Wealth Management, IR products, and FX. His expertise spans uncertainty quantification, generative modeling, and model risk management, with a knack for making models robust when data is messy and edge cases matter. He has a track record of translating cutting-edge research into production-ready tools used by large teams, mentoring PhD students, and aligning stakeholders on regulatory and risk standards. Based in Menlo Park, he blends deep physics and computational training (PhD, CMU; BTech, IIT Bombay) with practical frameworks for stress testing and failure analysis that expose rare, high-impact scenarios.
11 years of coding experience
Indian Institute of Technology BombayDoctor of Philosophy - PhD, Physics, Doctor of Philosophy - PhD, Physics at Carnegie Mellon University
English, Hindi, Punjabi
Github Skills (31)
routines10
density-estimation10
cosmology9
random-walk9
des9
correlation9
solver8
astrophysics8
particle8
astronomy7
mesh7
calculator7
gis7
scales7
covariance6
Programming languages (3)
Github contributions (5)
sukhdeep2/Public-code
Apr 2017 - Jun 2022
Contributions:58 pushes, 2 branches in 5 years 3 months
sukhdeep2/corr_pc
Jul 2021 - Jul 2023
Contributions:1 PR, 20 pushes, 1 comment in 1 year 11 months
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