Ryan Mastropaolo RyanMastropaolo

Hi there, I'm Ryan! 👋

I'm a Master's student in Financial Engineering at NYU Tandon School of Engineering with a background in Computer Science, Mathematics, and quantitative research. My interests lie at the intersection of financial markets, data science, and technology, with a particular focus on quantitative research, systematic trading, and machine learning in finance.

Outside of academics and research, I enjoy working out and cooking!

Education

New York University — Tandon School of Engineering

Master of Science in Financial Engineering | August 2026 – Present

Focused on quantitative finance, financial modeling, derivatives, statistics, and computational methods
Developing advanced skills in applying mathematics, statistics, and machine learning to financial markets

Sacred Heart University

Bachelor's Degree in Computer Science and Mathematics | August 2022 – May 2026

Mathematics concentration in Data Science
Completed senior capstone projects in both Computer Science and Mathematics
Conducted research spanning quantitative finance, artificial intelligence, financial sentiment analysis, and algorithmic trading

Current Focus

Quantitative Finance & Technical Interview Preparation

I am currently preparing for Summer 2027 quantitative finance internship opportunities, with a focus on quantitative research, quantitative trading, and related roles. My preparation combines technical problem-solving, quantitative finance fundamentals, probability, statistics, and programming.

Current Preparation:

NeetCode: Reviewing and strengthening the core data structures, algorithms, and problem-solving patterns commonly tested in technical interviews
LeetCode: Applying these concepts through algorithmic problem-solving, with practice across arrays, hash maps, two pointers, sliding windows, stacks, queues, heaps, trees, graphs, and dynamic programming
Quant Interview Prep: Working through A Practical Guide to Quantitative Finance Interviews (the "Green Book"), with an emphasis on probability, statistics, stochastic processes, brainteasers, and quantitative problem-solving
Financial Engineering: Continuing to develop my understanding of derivatives, mathematical finance, statistical modeling, and computational methods through my M.S. in Financial Engineering at NYU Tandon

Currently Seeking

I am currently seeking Summer 2027 quantitative finance internship opportunities, particularly in:

Quantitative Research
Quantitative Trading
Quantitative Analysis

Featured Projects:

SynTrade – Computer Science Senior Capstone

SynTrade is a hybrid multi-agent trading system that combining sentiment analysis and technical indicators. It introduces a validation layer that verifies heterogeneous signals before execution, improving risk-adjusted performance metrics.

Stack:

Python • Backtrader • LightGBM • Google Gemini API • pandas • NumPy • Matplotlib
APIs: Finnhub • FRED • NewsAPI.ai • Alpha Vantage • yfinance

Highlights:

Published in IEEE as SynTrade: A Hybrid Multi-Agent Trading System Combining Sentiment Analysis and Technical Indicators
Modular multi-agent trading system with a validation/critic layer before execution
Backtrader backtesting + baseline comparisons (buy-and-hold, technical-only)
Multi-source data pipeline (news + macro + fundamentals + technicals)
LightGBM models + Gemini LLM integration for sentiment/credibility scoring
Risk controls + logging/analytics (stops/exits, decision logs, performance visualizations)

Monte Carlo vs. Black–Scholes Mathematics Senior Capstone

This project compares Monte Carlo and Black–Scholes option pricing under identical geometric Brownian motion assumptions, using real market data to demonstrate the convergence.