At Alkami Technology, I automated a recurring classification workflow into a production XGBoost pipeline, processing tens of thousands of records and saving hundreds of hours. I also designed a controlled experiment on AI adoption across 350 engineers, using causal inference to inform company-wide adoption strategy.
I own end-to-end delivery of a self-serve decision-support platform built with TypeScript, React, and Python. I’ve also built data pipelines across engineering teams and designed a company-wide KPI framework and metric governance adopted with the CTO.
Earlier, at Alkami Technology, I redesigned customer targeting and built a quoting tool; at DTE Energy, I used risk-based segmentation and analytics to improve collections performance and generate revenue. I hold a Master of Applied Data Science and an MBA in Finance from the University of Michigan.
