Built and deployed a full-stack business management platform for an active retail clothing operation processing 500+ orders/month, covering client management, inventory, orders, payments, and financial reporting.
Migrated legacy sales history from Excel into a structured PostgreSQL database via a custom import script, preserving all historical transaction data across clients, products, orders, and payments.
Architected a scalable data layer with Next.js 16 App Router, Supabase/PostgreSQL, and server-side filtering + pagination — designed to handle years of order history without performance degradation.
Built interactive reporting dashboards (Recharts) with revenue breakdowns by store, product category, and time period.
Collected and processed real-time player tracking data across 84 MLS matches, logging ~1,200 data points per game with 94.8% accuracy to calculate advanced performance metrics (e.g., Ball trajectory) for live broadcast insights and post-match reports.
Calculate advanced performance metrics (e.g., expected goals [xG]) to support live broadcast insights and post-match reports.
Collaborate with data engineers and analysts to ensure accuracy, consistency and quality in large-scale sports datasets.
Book Recommendation System
University of North Texas
Denton, TX
02.2025 - 05.2025
Developed a book recommendation system in Python, applying Dijkstra's algorithm over a similarity graph to identify the 10 most relevant book recommendations per query in under 140 ms
Engineered the system to handle tens of thousands of user ratings, optimizing for scalability and performance.
Implemented core data structures such as hash maps, trees, to efficiently store and access user ratings and book metadata.
Education
Computer Engineering -
University of North Texas
Denton, TX
12-2026
Skills
C (proficient) – DS&A, OOP, memory management
Python – scripting & data analysis
Git/GitHub – branching, PRs, code reviews
Claude – agentic workflows, tool use, MCP integration