🎯 AI Engineer | Data Scientist | Sports Analytics Enthusiast
📍 Based in Austin, TX
🎳 Bowler | Gamer | Problem-Solver
I'm an AI Engineer and Data Scientist with a background in sports analytics, machine learning, and predictive modeling. With expertise in R, Python, and SQL, I specialize in sports performance analysis, data visualization, and AI-driven insights.
I have a Master’s in Sport Analytics, and my passion lies in using data to enhance decision-making, whether it's in basketball analytics, player development, or AI applications in sports.
📊 Key Skills:
- 🏀 Sports Analytics – Predictive modeling & player performance evaluation
- 🤖 AI & Machine Learning – NLP, deep learning, and model optimization
- 📊 Data Analysis & Visualization – R (Tidyverse), Tableau, SQL
- 💾 Data Management – SQL (queries, joins), CSV/Excel data handling
- 📈 Statistical Analysis & Modeling – Regression, Hypothesis Testing, ANOVA
- 🔧 Tech Stack – Python, R, SQL, Git, Salesforce, APIs
A fully automated system that creates 60-second NBA highlight recaps for every game using Python, LLMs, voice synthesis, and video editing tools. Designed for daily publishing on YouTube Shorts, TikTok, and Instagram Reels. Inspired by fast-paced, no-fluff sports coverage — reimagined for modern platforms.
A full-stack application that analyzes professional bowling tournament data to predict performance across different oil patterns and venues. Built with Python, Flask, React, and data visualization libraries.
Statistical analysis investigating the "contract year phenomenon" in the NBA, examining whether players perform better in the final year of their contracts. Implemented in R with advanced statistical modeling.
📝 Always learning, always improving. Open to collaborations in AI, sports analytics, and data science! 🚀