Jack Giovenco

I’m an aspiring sports data scientist with a strong foundation in computer science and an even stronger passion for uncovering meaning through numbers, especially in sports. I recently completed my Bachelor’s degree, where I focused heavily on data structures, algorithms, statistical modeling, and programming in Python, C++, Java, and R. Throughout my academic career, I’ve been drawn to problems that require both technical rigor and creative interpretation, especially when they relate to understanding athlete performance and development.

What excites me most is the opportunity to find deeper patterns in  data, patterns that aren’t always obvious but can reveal how a player is evolving, why a team is succeeding, or where hidden value exists. For my senior thesis, I built a predictive model to identify breakout Major League Baseball players using multi-year Statcast data. That project solidified my interest in applying analytics to real-world questions in player evaluation, forecasting, and team decision-making.

I’ve also had hands-on experience through internships where I worked with large datasets, automated workflows, and helped improve data-driven tools in Excel and Python environments. Long term, I hope to work in a baseball or sports analytics department where I can contribute to smarter scouting, development, or fan engagement through better models and sharper insights. I’ve always loved sports, but it’s the numbers behind them that truly motivate me to keep asking questions and pushing for answers.

I have experience in data-driven sports analysis, software development, and automation. I’ve built a predictive model for identifying breakout MLB players using advanced Statcast metrics, integrating multi-year performance data and similarity scoring. I’ve also completed a technical internship optimizing a custom Excel VBA system with automated data workflows and user interface enhancements. My skill set spans Python, R, C++, SQL, and Excel/VBA, with a strong focus on using data to solve real-world problems, especially those at the intersection of sports and analytics.

I earned my Bachelor’s degree in Computer Science with a focus on data science and statistical modeling. My coursework included Data Structures and Algorithms, Artificial Intelligence, Software Design, Data Mining (R), Big Data Analytics (R/Python), and Probability and Statistics.