Taha Shafaqat

Taha Shafaqat

Using Data to Empower and Inform Organizations

About Me

I am an Economics and Computer Science double major at the University of Washington Bothell. I am interested in using programming, economics, and financial mathematics to craft data-informed decisions for businesses, hospitals, government agencies, and nonprofit organizations.

Experience

June 2025 - Current

Digitalization Project Lead & Data Engineer

The House of Wisdom

Leading the development of a full-stack web app to automate internal operations. Engineered data pipelines to track student attendance and built dynamic dashboards for real-time performance monitoring.

July 2025 - Current

Math Tutor

Mathnasium

Provided individualized instruction to students from elementary to high school. Applied the Mathnasium Method to create engaging, structured learning plans tailored to each student's needs.

Projects

Minimum Wage Disparity Project

Designed a project analyzing the growing disparity between the U.S. minimum wage and the cost of living using a large BLS dataset. Utilized PostgreSQL to clean and format the data and developed a model illustrating how the minimum wage would appear if it had consistently tracked inflation. Incorporated average rent prices and compared them to CPI data to highlight how CPI fails to reflect the true cost of living for most Americans, culminating in data-driven storytelling.

Download Report (.pbix) →

Portfolio Optimization & Risk Analysis Project

Developed a data-driven model to optimize a stock portfolio using 10 years of historical price data from Yahoo Finance. Conducted Monte Carlo simulations with 50,000 portfolio weight combinations to identify allocations maximizing the Sharpe ratio (1.02) while minimizing risk (annualized volatility reduced by 18%). Visualized the efficient frontier to show optimal risk-return tradeoffs and recommended a portfolio mix projected to yield an annualized return of 22.3%.

View on GitHub →

EV Charging Infrastructure & Demand Forecasting

Built a system to find the best spots for new EV charging stations. This project used Python (Pandas, Scikit-Learn, Prophet) for analysis and forecasting, alongside SQL (PostGIS) for geospatial data. Data was integrated from government APIs and mapping services to ensure a comprehensive analysis. The result is an interactive dashboard that shows high-demand areas to help plan infrastructure spending wisely.

View on GitHub →

Core Skills

SQL Python (Pandas, NumPy, Scikit-Learn, TensorFlow) Statistics PowerBI Tableau Communication Storytelling Business Decision Making