Enthusiastic and quick to learn the latest techniques as an emerging quantitative researcher! Have held three quant-related internships, including two on the buy-side. Gained practical experience for multiple quant strategies (e.g., CTA, multi-factor) and alpha research. Adept at solving problems independently and collaboratively with data-driven methodologies and advanced programming skills. M.S. in Mathematics in Finance candidate at NYU Courant with a B.S. in Mathematics and a B.A. in Economics. Qualifications include:MATHEMATICS- Probability and statistics (e.g., OLS, MLE )- Stochastic process (e.g., Itô's lemma, Brownian motion)- Time series models (e.g., ARIMA, GARCH)QUANTITATIVE FINANCE- Interest rate models- Portfolio allocation methods (e.g., mean-variance optimization, Black-Litterman)- Market impact modelsDATA SCIENCE- Machine learning (e.g., decision tree, SVM)- Numerical methods (e.g., Monte Carlo, finite-difference, and fast Fourier transform)- Deep learning (studying this semester)PROGRAMMING SKILLS- Python, C/C++- Linux, Git- Data structures and algorithms