My name is Thomas, and I'm a student interested in Data Science, Frontend and Backend Development, and Quantitative Finance.

I am a Senior at Boston University, majoring in Data Science and minoring in Business.

I led the management and development for the website for my professional technology fraternity Kappa Theta Pi. This full-stack website uses react, node, express, firebase, and Mongodb. I also used a 3D model of BU's building of computing and data sciences and three-js to create an engaging animation in the rush page. Users can view different pages, including about us, all the brothers, e-board, and alumni of KTP, rush page, and a contact us page.

I led the management and development of a rush app for my professional technology fraternity Kappa Theta Pi. This full-stack app uses react native, node, express, firebase, and Mongodb. The app also uses Google Oauth sign-in for authentication for only Boston University emails. Once logged in, users have access to many things. They can see KTP's upcoming rush events. They can also see a list of other rushees, brothers, and board and their specific profiles. They are able to receive alerts from our eboard. Lastly, they can even customize their profile, adding a profile picture, interests, and social media. This app has helped a lot with KTP's rush process with more than 200 users on the app store!

Led a team to create a modern data pipeline solution in Azure that extracted, cleaned, loaded and analyzed covid-19 policy data to discover which polices were most effective in reducing covid cases. Created a galaxy schema for our data in an ODS, which was loaded in an Azure synapse warehouse and connected to PowerBI for statistical analysis and evaluation

Sports betting arbitrage ensures a profit by betting on all outcomes with different bookmakers to exploit odds discrepancies. While rare, these opportunities can be identified using tools like Odds-API. Implied probabilities help find favorable odds, and we found that odds variations during a game offered more chances for arbitrage. Despite frequent odds updates, our analysis confirmed that arbitrage opportunities do exist, especially as games progress.

As a lead quantitative developer, I'm involved in BU's Finance and Investments Club, specifically their quantitative division. I'm currently leading a team of 4 quantitative developers to create many technical analysis indicators (RSI, MACD, Bollinger bands, etc.) in Python to be used on S&P 500 stocks. We then utilize machine learning in TensorFlow on the different technical analysis indicators to find patterns between them and predict the future directionality of a stock using the past 90 days. This project will then be used to help choose stocks to invest in using the club’s management fund (~1.1M AUM). Learn more about this project below!

I wanted to see if there was a correlation between news headlines and stock prices. I used Python to scrape Google News for S&P 500 companies’ headlines. I then analyzed the average sentiment of 5 headlines for each company daily for 4 weeks using the NLTK library. Applied linear regression to the data to identify the correlation between a company’s sentiment score and stock profit as a percentage of a company. Learn more about this project below!

@joshleeds and I created a portfolio website for ourselves over the summer with HTML, CSS, and JavaScript. Working together as a team, we were able to create a website that showcased our coding skills and designs. We coded advanced animations, including a parallax scrolling effect, which created an engaging user experience. We also hosted the website using GitHub Pages and even created a domain for it. Learn more about this project below!