Dylan Pieper

Data Scientist

I work on data and software for social good. I started my career as a social psychologist, and now I lead data initiatives in research, program evaluation, and business operations. I design and develop principled and beautiful data tools across the full stack—from the applications, statistics, and visualizations people need to do their work to the models, pipelines, and systems that scale them—grounded in reusability, reproducibility, and trust.

I currently lead program evaluation and data analytics at UW-Madison to advance medical education. Across my career, I’ve transformed big and messy datasets—from APIs, surveys, and health records—into actionable insights presented to stakeholders. My work has reached audiences worldwide through open-source packages, talks, and publications.

My technical foundation is built on R, Python, and SQL, allowing me to seamlessly move from data extraction to advanced modeling. I leverage statistical inference, ML, and AI to turn complex datasets into predictive insights. To deliver these insights to stakeholders, I build and publish reports, dashboards, and interactive data products using Quarto and Shiny, maintaining deployment workflows through CI/CD pipelines on GitHub and GitLab and containers on Posit Connect and Azure.

Outside of data science, I have a deep appreciation for my wife, my dog, and nature. From paragliding to yoga, I find balance through exploring outer and inner landscapes. 🐾 🪂