People / Students / Class of 2027
Yifeng Chen is an aspiring data science professional with a strong foundation in statistics and analytics, currently pursuing his Master of Science in Machine Learning and Data Science at Northwestern University. He graduated Magna Cum Laude from New York University’s Leonard N. Stern School of Business with a bachelor’s degree in business, concentrating in statistics.
Yifeng gained valuable professional experience through internships at an exchange, a financial services company, and a public equity fund. He analyzed user behavior and market trends, constructed liquidity models, and implemented data-driven initiatives to optimize performance. In other roles, he standardized and processed large-scale datasets using Python and Excel, maintained dynamic databases tracking key performance indicators, performed in-depth data analysis for risk assessment, and delivered visualization reports to support decision-making. In academic projects, he applied Python for comprehensive data science workflows on market datasets, including data cleaning, exploratory data analysis, feature engineering across trend, momentum, volatility, and liquidity dimensions, and model development. He compared Logistic Regression, Support Vector Machine, Random Forest, and XGBoost models through model tuning and backtesting frameworks, while using R to build ARIMA-GARCH models for time series forecasting with residual diagnostics and statistical validation.
Yifeng possesses strong technical skills in Python, R, SQL, data visualization, A/B testing, and tools such as Tableau and Excel. As he begins the MS in Machine Learning and Data Science program at Northwestern University, Yifeng is eager to deepen his expertise in data science and advanced analytics, leveraging rigorous technical methods to solve complex data problems and create meaningful impact.
