Currently an Extern @Breaking Games
I specialize in turning messy data into clear, actionable insights through innovative database solutions.
Discover how I leverage SQL and database architecture to create impactful analytics solutions.
Breaking Games · · ✅ Verified by Extern
Turn six messy CSVs into an analytics database and a Q4 dashboard that drives real business decisions. SQL + Claude.
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Developed a Cellular Automata Simulation in MATLAB to model the epidemiological spread of infectious diseases (SIR model), using von Neumann neighborhood logic to calculate transmission dynamics between susceptible, infectious, and immune populations; engineered a deterministic state-transition engine with probabilistic initialization and real time animation, analyzing how varying infections rates and immunity impact virus propagation across a population grid
I specialize in turning messy data into clear, actionable insights through innovative database solutions.
I am a senior at Colby College majoring in Computer Science with a focus on Data Analytics. My experience includes transforming complex datasets into actionable insights, particularly through my current externship in SQL and database architecture.
Externships
SQL & Database Architecture Externship with Breaking Games
Breaking Games
Experience
Data Research Consultant
Pryzm.io · April 2026- Present
Associate Barista Manager
Starbucks · June 2025- Present
Associate Project Manager
VOA · June 2025- August 2025
Consumer Insights Intern, Extern
Beats by Dre · May 2025- August 2025
Marketing Associate
Fizz Inc · February 2023- May 2024
Education
Colby College, Waterville, ME
Bachelors of Arts in Computational Biology | Minor in African American Studies · Class of 2026
Skills
Breaking Games ↗
Turn six messy CSVs into an analytics database and a Q4 dashboard that drives real business decisions. SQL + Claude.
During my SQL and Database Architecture externship with Breaking Games, I transformed six disorganized CSV files into a functional analytics database and developed a Q4 dashboard. This project aimed to support data-driven decisions in the e-commerce sector, leveraging SQL and advanced analytical tools.
In my work at Breaking Games, I took the initiative to familiarize myself with the company's data landscape and e-commerce operations. Below are the key steps I completed during the externship.
Project 1: Getting Into Breaking Games' Raw Data
I collaborated with the team to assess the existing data landscape at Breaking Games. I explored six key data sources affecting e-commerce operations, established a SQLite database, and executed my initial SQL queries. By week's end, I was able to provide answers to data questions in seconds,
Developed a Cellular Automata Simulation in MATLAB to model the epidemiological spread of infectious diseases (SIR model), using von Neumann neighborhood logic to calculate transmission dynamics between susceptible, infectious, and immune populations; engineered a deterministic state-transition engine with probabilistic initialization and real time animation, analyzing how varying infections rates and immunity impact virus propagation across a population grid
Developed a Cellular Automata Simulation in MATLAB to model the epidemiological spread of infectious diseases (SIR model), using von Neumann neighborhood logic to calculate transmission dynamics between susceptible, infectious, and immune populations; engineered a deterministic state-transition engine with probabilistic initialization and real time animation, analyzing how varying infections rates and immunity impact virus propagation across a population grid
Implemented Adaline from scratch using gradient descent and built MLP’s with hidden layers and backpropagations, applying ReLU and sigmoid classifications; explored Deep Dream and learned CNN architecture on image sets to evaluate model performance
Implemented Adaline from scratch using gradient descent and built MLP’s with hidden layers and backpropagations, applying ReLU and sigmoid classifications; explored Deep Dream and learned CNN architecture on image sets to evaluate model performance
Implemented PCA for dimensionality reduction and K-Means clustering for image colorspace compression using NumPy, Matplotlib, and OpenCV; interpreted elbow and loading plots to evaluate model fit and used scaling, translating, rotation, projection transformations to explore high-dimensional biological datasets
Implemented PCA for dimensionality reduction and K-Means clustering for image colorspace compression using NumPy, Matplotlib, and OpenCV; interpreted elbow and loading plots to evaluate model fit and used scaling, translating, rotation, projection transformations to explore high-dimensional biological datasets
Applied fundamental algorithms (Dijkstra's, (BFS), (DFS), and tree traversals) to build real world projects such as a Blackjack engine, Conway’s Game of Life, Sudoku, Grid Search, Server Farm Simulator, etc.
Applied fundamental algorithms (Dijkstra's, (BFS), (DFS), and tree traversals) to build real world projects such as a Blackjack engine, Conway’s Game of Life, Sudoku, Grid Search, Server Farm Simulator, etc.