Ritesh Kumar
Quantitative Developer
India
Summary
👤
Senior🎓
Top SchoolRitesh Kumar is a quantitative developer with eight years of experience building low-latency C++ trading infrastructure and Python research tooling for top-tier prop trading firms, most recently at Tower Research Capital and now at Graviton Research Capital. An IIT Kanpur graduate in EE and CSE, he blends rigorous mathematical thinking with production-grade software engineering—previously contributing backend systems at a fast-growing fintech startup and intern-level ML and systems research at Microsoft, NUS and Max Planck. He is an active open-source contributor (GSoC'19) to SymPy, where he improved statistical and physics modules and added extensive test coverage, reflecting a focus on correctness and reproducibility. Comfortable moving between algorithm design, ML research and distributed production systems, he brings both theoretical depth and practical delivery to quantitative software problems. An interesting quirk: he has reduced sampling complexity in symbolic statistics work while also shipping large-scale real-time anomaly detection and trading systems, showing a rare span from symbolic math to low-latency finance.
8 years of coding experience
1 year of employment as a software developer
Indian Institute of Technology Kanpur
English, Hindi
Github Skills (6)
computer-algebra10
pytest10
python10
testing10
math9
mathematics9
Programming languages (9)
Github contributions (5)
sympy/sympy
Mar 2019 - Aug 2019
A computer algebra system written in pure Python
Role in this project:
QA Engineer / Test Automation Engineer
QA Engineer / Test Automation EngineerContributions:123 commits, 51 PRs, 276 comments in 5 months
Contributions summary:Ritesh primarily contributed to the project by adding tests. Their commits focused on creating new test cases for the `physics/optics` and `physics/mechanics` modules, specifically targeting functionality in `waves.py`, `medium.py`, `utils.py`, `particle.py`, and `rigidbody.py`. Additionally, they added tests related to distributions within the `sympy/stats` directory. These tests appear to be aimed at ensuring the accuracy and reliability of the code within the project.
mathpythonsciencecomputer-algebra-systemalgebra
ritesh99rakesh/pyMIDAS
May 2020 - Aug 2021
Python implementation of MIDAS: Microcluster-Based Detector of Anomalies in Edge Streams
Contributions:1 review, 7 commits, 6 PRs in 1 year 4 months
pythonpython-implementationfraud-detectionstreamsanomaly-detection
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