We are
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Thomas Yousef
EDUCATION
Boston University Expected 2026
B.S. in Data Science,
Minor in Business Administration
Joshua Leeds
EDUCATION
Boston University Expected 2026
B.S. in Data Science,
Minor in Business Administration
We are Passionate Data Science students attending Boston University.
With an interest in technology, data, and business, we are constantly exploring the world of data analytics, machine learning, and artificial intelligence.
Through our coursework, practical experience, and personal projects, we have developed a strong foundation in statistical analysis, programming, and data visualization techniques.
Explore skills and experiences that we share as well as ones unique to each of us
Python
Java
CSS
HTML
Java Script
GIT
VS Code
X Code
Py Charm
Azure
SK Learn
TensorFlow
Full-stack mobile app for Kappa Theta Pi built with React Native, Expo, Node.js, Firebase, and MongoDB. Serves 300+ active users with 1,000+ daily database invocations via REST. Integrated Google OAuth with persistent secure sessions.
Designed and developed the official Kappa Theta Pi Boston University chapter website. Built with React and TypeScript, the site serves as the public face for recruitment, events, and member resources for 300+ chapter members.
Web app that analyzes user stock portfolios using volatility scoring and historical data to recommend lower-risk, same-sector substitutes. K-means clustering on S&P 500 via dividend yield, volume, and profit margin to predict future portfolio performance.
Python arbitrage detection system using the Odds-API to aggregate live betting odds across 15+ sportsbooks and 70 sports. Collects and compares sportsbook data every 5 minutes in real time, identifying timing-based arbitrage opportunities across platforms.
Led a team to build a data pipeline on Azure that extracted, cleaned, loaded, and analyzed COVID-19 policy data to identify the most effective interventions in reducing case counts. Created a galaxy schema in an Azure ODS loaded into an Azure Synapse warehouse, connected to PowerBI.
Engineered a sentiment analysis pipeline with Python and NLTK to scrape and analyze 100 daily headlines per S&P 500 company. Discovered strong positive sentiment–return correlations in 60+ companies, demonstrating the predictive potential of news sentiment in equity performance.
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Member of the Alpha Class of KTP at Boston University. Built and maintain the official KTP mobile app (React Native · Node.js · Firebase · MongoDB), serving 300+ active members with 1,000+ daily database invocations. Also designed and developed the official KTP Boston website (ktp-bostonu.com) using React and TypeScript.
Assistant VP of Quantitative Research — organized and delivered lectures to junior developers on Binomial Options Pricing Models, Modern Portfolio Theory, and Monte Carlo Methods. Led quantitative finance projects each semester, presenting findings to club members, the executive board, BU professors, and industry professionals.
Built and tuned an XGBoost regression model to forecast Chase's total daily customer spend across all debit and credit card transactions nationwide, applying feature engineering and time series techniques. Achieved 1.5% and 1.9% error across two testing rounds, enabling better strategic planning and anomaly detection.
Developed scalable web components using React.js and Node.js, and designed backend architecture with AWS SAM integrated with DynamoDB for efficient data storage. Executed end-to-end testing to validate functionality, data accuracy, and alignment with business requirements.
Organized lectures for junior developers on complex finance topics including Binomial Options Pricing Models, Modern Portfolio Theory, and Monte Carlo Methods. Led multiple projects each semester presented to club members, the executive board, BU professors, and industry professionals.
Led analysis of Xfinity subscriber base to identify potential future growth and marketing opportunities. Conducted data discovery using SQL across multiple databases to build comprehensive data sources and tables. Created descriptive visualizations with Tableau and presented findings to senior management.
Host weekly office hours to help students with Python, Rust, data structures, algorithms, and data analysis. Grade assignments and provide students with advice and feedback.
Lead a quantitative finance project with a team of 4 developers to research the NYSE and other global markets using Python; utilize NumPy, pandas, Matplotlib, and yfinance libraries. Work with other groups and projects to analyze, predict, and further research the stock market.
