I build machine learning systems from beginning to end with an eye towards the end product. From exploratory analysis and feature engineering through production-ready deployment with containerized infrastructure, monitoring, and CI/CD, I have the knowledge and skills to build and deploy models strategically. Recently, I trained a CatBoost model that predicts used-car prices within ~$1,300 at the median across 243k vehicles and packaged it as a production-ready API with FastAPI, Docker, Kubernetes, Prometheus + Grafana monitoring, and automated testing via GitHub Actions. I care about building models that are validated, documented, and ready to serve real traffic.

What sets me apart from most ML engineers is that I've made high-stakes business decisions with data. As Director of Strategic Planning for a national retail company, I oversaw marketing investments, store expansion, and promotion optimization, enhancing the company's analytics capabilities to improve how resources were allocated, especially for long-term initiatives where results take time to materialize. That experience gave me a deep understanding of what data-driven strategy actually looks like from the decision-maker's seat, not just the analyst's.

One of the strengths I bring to any organization is my curiosity and drive to continuously learn and apply new technologies to solve complex business problems. I've built and tuned AI models, implemented optimization with tools like Gurobi to identify global minima and maxima for strategic decision-making, and developed production-grade Python applications, earning a 4.0 GPA in my Master of Science in Business Analytics at William & Mary along the way. After completing my Python course, I continued to tutor others in programming, which not only strengthened my students' technical competencies but also reinforced mine.

I earned my undergraduate degree from Georgetown University's School of Foreign Service, majoring in Science, Technology, and International Affairs. Before studying Mandarin Chinese formally, I had already begun teaching myself the language and passed early fluency exams. At Georgetown, I deepened that foundation and successfully passed an advanced fluency exam, a reflection of the same persistence and self-directed learning I bring to every technical challenge. Having lived in Jackson Hole, Wyoming, Northern Virginia, and China, I've developed an appreciation for diverse perspectives and an ability to collaborate across cultures.