Technical

Building on top of AI APIs and getting reliable behavior out of them, including fallbacks for when the model or key is unavailable.

Getting from idea to working demo fast, and making the demo reliable enough to show live.

Structuring messy inputs until the pattern shows itself.

The query and scripting layer under the analysis work. Three Python builds:

Policy-to-control mapping at JPMC. With an applied AI/ML team, I built a tool that lets regulatory controllers automate the manual assignment of policies to risks to controls. It was built in Fusion, a Python-based tool, and I wrote the code.

Predictive Data Analyzer (Python + machine learning). I built k-means and linear-regression models to predict Yelp ratings, then translated the technical outputs into business insights for potential recommendation-engine use. I also built a spatial visualization dashboard to surface data-driven restaurant clusters and improve user discovery within those clusters.

OOP Simulation (Python). I modeled multi-agent decision systems using inheritance and polymorphism to simulate adaptive behavior under dynamic constraints, demonstrating architectural thinking and principles that apply to ML pipelines.

Design as the translator for complex products. I designed a family blockchain wallet mockup in Figma, prototyped end to end.

As a Global Finance and Business Management intern in Summer 2026, I projected headcount and budget forecasts for call centers and operations teams, working in Excel with Dodeca and Essbase.