Resume

Candidate for Bachelor of Science in Computer Science and Business Administration GPA: 3.8

Honors/Activities: Treasurer, NU Systematic Alpha; Dean's List

Relevant Coursework: Discrete Structures, Introduction to Databases, Program Design & Implementation, Business Statistics, Financial Management

Languages: Python, C++, Java, Rust, JavaScript, TypeScript, SQL, Kotlin

Frameworks & Libraries: React, Next.js, Redux, Electron, TensorFlow, Keras, Pandas, NumPy

AI/ML: Open-weight models, Ollama, LM Studio, Unsloth, ComfyUI, MCP

Developer Tools: Git, AWS (EC2), PostgreSQL, Azure DevOps, IntelliJ, Eclipse, PyCharm, Xcode

BlackRock | San Francisco, CA

Morgan Stanley | Derivatives Sales Trading | New York, NY

Wellington Management | Boston, MA

• Regressed Blackstone private equity fund returns against public-market indices to estimate replicating index weights for a pooled vehicle supporting pre-seeded investments.
• Built a Python AI agent and MCP server for the risk portal, cutting token usage with local SQL caching, session persistence, and data-resolution filtering while automating stress tests and portfolio risk analysis.
• Developed post-shock equity-option exposure analytics and a Shapley decomposition tool that attributes changes in portfolio risk to positioning versus factor-level movements over time.

Zeal IT Consultants | Dallas, TX

• Developed the frontend for Trinity Industries' Asset Management System using React and Next.js.
• Increased team delivery capacity by 300% within one release cycle, accelerating the project timeline by 4 weeks.
• Decreased page load times by 94% by migrating from MobX to Redux and implementing server-side rendering.

Event-Driven Implied Volatility Mispricing | Python, Polygon.io | Report January 2026 – March 2026

• Built a Python backtesting framework extending Gao, Xing & Zhang (2018) to identify event-driven implied volatility (IV) mispricings across 4 event types, processing 80,000+ option observations.
• Generated sector-level long/short straddle signals achieving a 63% win rate and 3.62% average return per trade out-of-sample on Technology earnings, and a 74% win rate with 10.81% ROI on FOMC events in 2025 testing.

Prediction Market Trading | Rust, AWS | Portfolio December 2025 – Present

• Built a real-time prediction market pricing model in Rust on AWS EC2 for low-latency API access.
• Achieved a 1.2 net adjusted Sharpe ratio, 40% total return, and 10% maximum drawdown over two months.

PM-Trading Desk | Python, WebSockets | GitHub September 2025 – Present

• Built a WebSocket prediction market trading app handling 500+ updates per second with sub-50ms order execution.
• Implemented a smart order router spanning Polymarket and Kalshi, achieving 2–5% average price improvement per trade through cross-exchange execution.

Hackathons, Reading, Rubik's Cube, Chess, Poker, Baseball, Blogging, Football, Working Out, Watches, Shoes