CS student at Northeastern. I work mostly on systems and quantitative tooling — the overlap between low-level performance engineering and applied math.
Primary: C++, Python, Rust, Java
Familiar: Julia, Kotlin, JavaScript, Ruby
Tooling: Linux, Docker, Git, React
Data/ML: pandas, numpy, scikit-learn, PyTorch
Systems — operating systems, distributed systems, low-latency architecture, performance optimization.
Quant — algorithmic trading, market microstructure, backtesting, risk modeling.
Math & finance — probability, stochastic calculus, optimization; derivatives pricing and factor models.
ML — time-series forecasting and RL applied to trading.