LinkedIn Profile Growing up in an economy where uncertainty was part of everyday life pushed me to understand how markets work. That curiosity first led me to quantitative finance: using data, models, and disciplined reasoning to bring structure to noisy markets. Before MSCF, I ranked in the top 0.01% nationally in mathematics and science, then pursued a double major in Industrial Engineering and Computer Engineering. My interests are in quantitative research and systematic trading, especially roles where mathematical modeling and machine learning can support investment decisions. At Mastercard, I built machine learning pipelines for financial applications, working with large- scale transaction data, feature engineering, embeddings, and XGBoost-based predictive models. I also independently developed a cross-sectional equity selection andback-testing system across 500 stocks, using machine learning, engineered momentum and volatility features, and rolling out-of-sample evaluation to generate probability-ranked trading signals. My experiences at Bain & Company, in FX trading, and in asset management projects also taught me how technical work, attention to detail, and clear communication matter when decisions must be made under ambiguity. I bring a combination of technical training, emerging-market perspective, and practical experience translating data into financial insight. I am always glad to connect with professionals in quantitative research, systematic investing, and global markets.
