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Data Scientist fueled by a long-standing obsession with mathematical patterns. My expertise spans Machine Learning, Deep Learning, and Statistical Analysis, but my approach is shaped by my background as a basketball player. That experience instilled a team-first mentality and a drive for precision that I bring to every model I build. I specialize in transforming messy, high-dimensional data into clear, strategic insights.

My primary workflow involves Python and PyTorch for model development, supported by PostgreSQL for robust data management. To ensure these models perform in production, I utilize Docker for containerization and Apache Airflow for workflow automation, all hosted and scaled within the AWS ecosystem.

I bridge the gap between high-level mathematics and real-world impact. Whether I’m decoding player performance in sports analytics, architecting NLP pipelines, or building predictive models, my focus remains on precision and production. I don't just deliver accuracy scores; I deliver robust, engineering-first solutions that transform 'big data' into a clear strategic roadmap.