Rajeev Godse

Quantitative Trader

New York, New York, United States
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Summary

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Senior
🎓
Top School
Rajeev Godse is a quantitative trader and Carnegie Mellon-trained computer scientist with eight years of experience bridging algorithmic research, ML, and production software. Currently at Jane Street, he has progressed from intern to trader, previously extending OCaml compilers and building a query language for temporal logic while also delivering high-impact ML infrastructure at Meta. His background includes satellite and hyperspectral imaging projects that fused domain knowledge with machine learning to produce real-time onboard processing and novel multi-resolution search techniques. A seasoned teaching assistant and curriculum developer, he brings clear technical communication and pedagogy to complex systems. Known for combining rigorous mathematical thinking with practical implementation, he thrives on turning theoretical ideas into low-latency, real-world trading and ML systems.
code9 years of coding experience
job2 years of employment as a software developer
bookHigh School Diploma, High School Diploma at Fox Chapel Area High School
bookManagement & Technology Summer Institute at UPenn, Management & Technology Summer Institute at UPenn at Jerome Fisher M&T Program
bookBachelor of Science - BS, Computer Science, Bachelor of Science - BS, Computer Science at Carnegie Mellon University
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Stackoverflow

Stats
1reputation
150reached
0answers
1question
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Github Skills (13)

ocaml9
ios6
datasets6
tensorflow5
machine-learning5
javascript3
numpy3
react3
backend3
jax3
vite1
music1
android1

Programming languages (4)

TypeScriptOCamlJavaScriptPython

Github contributions (5)

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rajgodse/flambda-backend

Jul 2023 - Aug 2023

The Flambda backend project for OCaml
Contributions:10 reviews, 6 PRs, 202 pushes in 1 month
backendocaml
raaidrt/parser

Dec 2023 - Dec 2023

A monadic parser combinator
Contributions:2 reviews, 22 comments in 1 day
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