About

My background is in public-service and regulated program environments, where I have worked with complex cases, policy requirements, stakeholder communication, training, and process improvement. That experience shapes the way I approach analytics: I tend to focus on problems where data needs to support real operational decisions, not just produce a model or visualization.

My technical work centers on public programs, regulatory compliance, healthcare access, economic stability, and service delivery. I use SQL, Python, statistical analysis, and machine learning to build reproducible workflows for monitoring performance, identifying risk, evaluating outcomes, and translating complex data into information that decision-makers can actually use.

I am particularly interested in the intersection of data science and public-sector operations, including compliance analytics, policy analysis, program evaluation, and responsible AI-assisted decision support.