Currently an Extern @Breaking Games
I explore consumer behavior through data analysis, aiming to transform insights into impactful strategies for e-commerce businesses.
🟢 Open to workExplore my projects focused on e-commerce data analysis, where I leverage tools like Google Analytics and Shopify to drive business growth.
Breaking Games · ✅ Verified by Extern · ⏱️ In progress
A Breaking Games externship focused on analyzing e-commerce and marketing data to understand how online shoppers move from awareness to purchase.
Analyzed 2,000 CFPB consumer complaint records using R and Tableau to identify complaint trends, response patterns, and regulatory risk factors across major credit bureaus. Developed a supervised decision tree model and engineered complaint classification features to automate the routing of consumer disputes through regulatory resolution workflows, including dispute management, fraud alerts, debt verification, and human escalation protocols. Integrated decision-tree business logic into a GPT4All chatbot, creating an AI-driven complaint triage framework designed to improve response efficiency, support compliance requirements, and reduce manual case-routing efforts.
As part of a team project in my Principles of Management class, I helped design, test, and refine a simulated frozen-treat business, using rapid prototyping and data analysis to inform strategic decisions. The project explored startup planning alongside an interactive food truck simulation, allowing us to test various business models across products, locations, and vehicle types (pushcart vs. truck) in a dynamic, data-rich environment.
Developed a robust, analytics-ready relational database to support the NFL's strategic and operational decision-making. The project focused on modeling and organizing critical data domains-including Teams, Players, Coaches, Games, Stadiums, and Ticket Sales-to provide league executives with meaningful insights into league performance and operations.
I explore consumer behavior through data analysis, aiming to transform insights into impactful strategies for e-commerce businesses.
I am an aspiring data analyst with a passion for understanding consumer behavior in e-commerce. Currently engaged in an externship with Breaking Games, I am diving into the world of online shopping analysis to uncover insights that can drive sales and improve customer experiences.
Externships
Breaking Games E-Commerce Data Analysis & Strategy Externship
Breaking Games
Experience
Extern
Breaking Games · Jul 2026 - Present
Digital Support
Koala Web Design · Jun 2026 - Present
Crew Member
Dunkin Donuts · Aug 2021 - May 2022
Education
University of Georgia
Management Information Systems · Class of 2026
Skills
✅ Verified by Extern · ⏱️ In progress
A Breaking Games externship focused on analyzing e-commerce and marketing data to understand how online shoppers move from awareness to purchase.
The work analyzed exported e-commerce and advertising data alongside a personal purchase narrative to map a gym-shoe shopping journey. The project produced a step-by-step funnel table documenting touchpoints, emotions, and decisions at each stage, plus a channel-level comparison of pageviews, add-to-cart, bounce, and checkout rates. The analysis found that Google referrals had higher engagement
I produced a step-by-step funnel table mapping a gym-shoe purchase journey and a comparative dataset of pageviews, add-to-cart, bounce, and checkout rates by referral source, noting that Google referrals outperformed Facebook on engagement and conversions.
I mapped my buying journey from awareness to conversion for a new pair of gym shoes, recorded what happened at each funnel stage, noted feelings and touchpoints, and produced a step-by-step funnel table showing the decisions and final purchase.
I examined exported site data, filtered by referral source, and compared pageviews, add-to-cart, bounce and checkout rates. I found Google referrals showed higher conversion and engagement than Facebook, which had high bounce and lower conversions.
Analyzed 2,000 CFPB consumer complaint records using R and Tableau to identify complaint trends, response patterns, and regulatory risk factors across major credit bureaus. Developed a supervised decision tree model and engineered complaint classification features to automate the routing of consumer disputes through regulatory resolution workflows, including dispute management, fraud alerts, debt verification, and human escalation protocols. Integrated decision-tree business logic into a GPT4All chatbot, creating an AI-driven complaint triage framework designed to improve response efficiency, support compliance requirements, and reduce manual case-routing efforts.
As part of a team project in my Principles of Management class, I helped design, test, and refine a simulated frozen-treat business, using rapid prototyping and data analysis to inform strategic decisions. The project explored startup planning alongside an interactive food truck simulation, allowing us to test various business models across products, locations, and vehicle types (pushcart vs. truck) in a dynamic, data-rich environment.
Developed a robust, analytics-ready relational database to support the NFL's strategic and operational decision-making. The project focused on modeling and organizing critical data domains-including Teams, Players, Coaches, Games, Stadiums, and Ticket Sales-to provide league executives with meaningful insights into league performance and operations.