Shoaib Khan

Highly motivated and detail-oriented George Brown College graduate with a strong educational background in Artificial Intelligence. Seeking a challenging Data Analyst Intern role in Toronto, where I can apply and enhance my skills in data analysis, Python, SQL, and visualization. Eager to gain practical experience in a professional setting, I am committed to utilizing my analytical and problem-solving abilities to contribute to a dynamic organization's data-driven decision-making processes and learn from experienced professionals in the field.

Portfolio Optimization Using Machine Learning

Technologies: Python, pandas, NumPy, scikit-learn, yfinance, Matplotlib, NetworkX
Concepts: Machine Learning, Factor Analysis, Portfolio Management

• Developed a stock portfolio optimization tool using Python to analyze S&P 500 stocks, employing machine learning techniques to enhance selection and risk management.
• Integrated multifactor models including volatility, beta, and momentum to rank and select top-performing stocks, and applied Principal Component Analysis (PCA) for dimensionality reduction.
• Implemented K-Means clustering for asset categorization and NetworkX for graphical analysis to assess stock correlations, aiding in robust portfolio diversification.
• Optimized asset allocations using Mean-Variance Optimization to maximize the Sharpe Ratio, significantly improving the risk-adjusted returns.
• Evaluated portfolio performance and diversification through Effective Number of Constituents (ENC) and Bets (ENB) calculations, demonstrating advanced analytical capabilities in financial modeling.