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Jane Street Intern CV

The document outlines an individual's academic background, achievements, skills, work experience, and research projects. They are currently pursuing a B.Tech in Computer Science at IIT Delhi with a high CGPA and have notable accomplishments in competitive programming and mathematics. Additionally, they have experience in quantitative trading and have developed a trading bot that achieved significant simulated returns.

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akushai094
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620 views1 page

Jane Street Intern CV

The document outlines an individual's academic background, achievements, skills, work experience, and research projects. They are currently pursuing a B.Tech in Computer Science at IIT Delhi with a high CGPA and have notable accomplishments in competitive programming and mathematics. Additionally, they have experience in quantitative trading and have developed a trading bot that achieved significant simulated returns.

Uploaded by

akushai094
Copyright
© © All Rights Reserved
We take content rights seriously. If you suspect this is your content, claim it here.
Available Formats
Download as PDF, TXT or read online on Scribd
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Your Name

Your Location | your.email@example.com | LinkedIn/GitHub

Education
Indian Institute of Technology (IIT) Delhi
B.Tech in Computer Science & Engineering (Expected 2027)
CGPA: 9.8/10

Achievements
- Facebook Hacker Cup - Global Top 10
- Codeforces - 2800+ rating (Red Coder)
- CodeChef - 6-star rated
- JEE Advanced - AIR 2
- KVPY - Rank 2
- INMO - Awardee
- IOI (International Olympiad in Informatics) - Silver Medalist
- IOAA (International Olympiad on Astronomy & Astrophysics) - Gold Medalist

Skills
- Programming: C++, Python, Rust
- Mathematics: Probability, Linear Algebra, Combinatorics
- Trading Concepts: Market Making, Statistical Arbitrage, Options Pricing

Work Experience
Jane Street Quant Trading Challenge - Finalist
Developed a high-frequency trading bot in Python, achieving 15%+ simulated returns.

Research & Projects


- Built a reinforcement learning-based trading strategy using Q-learning.
- Analyzed market microstructure using high-frequency order book data.
- Participated in a Kaggle competition for stock price prediction (Top 1%).

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