π MS in Financial Engineering @ NYU Tandon
π Aspiring Quantitative Researcher / Developer | Focused on trading strategies, derivatives pricing, and data-driven alpha generation.
π» Background in software engineering, machine learning, and financial modeling.
- Designing and backtesting systematic trading strategies in Python/C++
- Studying stochastic processes, probability, and derivatives pricing models
- Exploring high-performance computing applications in quantitative finance
- Contributing to open-source finance/data-science libraries
Programming: Python (NumPy, Pandas, SciPy, scikit-learn), C++, SQL
Finance Libraries: QuantLib, yfinance, Bloomberg API (basic)
Data & Visualization: Jupyter, Matplotlib, Plotly
Systems: Git, Linux, Bash, Docker
- Secure a Summer 2026 Quant Internship
- Publish polished quant research + trading repos
- Expand skills in C++ for pricing & HPC
- Contribute to open-source finance libraries
I enjoy lifting weights, exploring New York City, listening to finance/tech podcasts, and experimenting with plant-based recipes π±.
