Shlok Patel shlok-p07

Hey, I'm Shlok Patel

Quant-focused software engineer with interests in trading systems, derivatives, and ML
Building reinforcement learning–based hedging strategies and backtesting systems
Experience across full-stack development, real-time systems, and data pipelines
Passionate about combining finance + engineering to solve complex problems

Disrupt – The FinTech Initiative at Northeastern University — Boston, MA
Quantitative Analyst | Jan 2026 – Present

Developing quantitative trading strategies (pairs trading, mean reversion, momentum) using $50K simulated capital
Analyzing research in equity markets (statistical arbitrage, factor investing, market microstructure)
Building Python backtesting pipelines across 10M+ historical data points

Student Government Association (SGA) at Northeastern University — Boston, MA
Software Engineer | Jan 2026 – Present

Developing a platform serving 5,000+ students with centralized resources and leadership information
Architecting scalable UI using TypeScript, React, and Next.js
Contributing through PR-based development, reviews, and feature iteration

NU Oasis — Boston, MA
Project-Series Mentor | Jan 2026 – Present

Mentoring teams to design and deploy real-world software solutions
Guiding API integration and full-stack development using React, Node.js, and TypeScript

Rainfall Learning – Live Tutoring — Boston, MA
Software Engineer | Nov 2025 – Present

Leading front-end development with 15+ engineers for real-time collaborative coding platform
Implementing CRDT-based real-time collaboration in an embedded IDE
Improved reliability by 15% through Docker + CI/CD enhancements

Oasis — Boston, MA
Front-End Software Engineer (Team Lead) | Sep 2025 – Dec 2025

Developed a full-stack web application with a team of 5 to have real-time live menus and ratings for the students through integrating an API to keep everything up to date from university dinning halls’ database
Designed webpages and overall functionality of the app to have a welcoming user interface using React, tailwind CSS and Figma (prototypes)

Reinforcement Learning for Derivative Hedging
Personal/Research Project | In Development

Explores adaptive option hedging strategies using reinforcement learning, moving beyond classical delta-based hedging.
Objectives: Minimize portfolio risk and drawdowns, account for transaction costs, and compare RL-based hedging with traditional delta hedging.
Methods: Custom OpenAI Gym environment, PPO-based RL agent, simulated market dynamics with option Greeks.

	patel.s15@northeastern.edu
	www.shlokpatelportfolio.live
	linkedin.com/in/-shlokpatel