About Me

I am a Data Scientist and Machine Learning Engineer with over a decade of experience building resilient data systems for the financial and energy sectors. My journey to data science was built on a foundation of discipline and rigor, starting with my service in the US Army Infantry and sharpened through a Master’s in Applied Statistics and a Bachelor’s in Mathematics.

Throughout my career, I’ve seen firsthand how siloed information can cripple an organization. That is why I champion a strictly "definition-driven" approach to data architecture. Whether I am architecting complex Snowflake environments, engineering predictive charge-off models, or building intuitive Streamlit applications, my goal is always the same: to cut through the noise and establish a governed, single source of truth.

I combine advanced statistical methodologies with modern Generative AI frameworks like LangChain to solve complex business problems. My work is driven by a personal commitment to integrity, honesty, and respect—values that ensure the systems I build are not only innovative, but reliable and mathematically sound.