I’m a public health data scientist and informaticist working at the intersection of messy data, shifting inputs, and the challenge of making better decisions from imperfect information. I’m currently finishing the remaining project requirements for my MPH in Public Health Data Science at the University of Minnesota School of Public Health and working with the Center for Public Health Systems.
My work focuses on building end-to-end data systems that turn fragmented, inconsistent sources into coherent, reliable outputs that can actually be analyzed. I’m drawn to pipelines and system design because they feel like large problem-solving puzzles, where I can creatively design structures that turn messy data into something people can actually analyze. Recent projects include developing pipelines for large federal health-funding datasets, creating structures that align internal grant data with public reporting systems, and building visual and interactive tools that help people develop intuition for complex patterns and statistical relationships. I’ve also begun developing a large-scale job aggregator for public-sector roles across the U.S.