Dylan Pieper

Data Scientist

You can call me a social scientist, data scientist, or data and analytics engineer—but really, I’m a technical lead and support professional for research, program evaluation, and strategic business operations in the non-profit sector. I thrive in fields with a human-centered mission and love collaborating with teams to create insightful data tools that look beautiful and are easy to use. I work across the full stack—from the visualizations, reports, and dashboards people interact with to the models, pipelines, and cloud architecture that scale them—with reproducibility and open science as my core values.

I currently lead data strategy at UW-Madison advancing medical education. Across my career, I’ve transformed big and messy datasets—from APIs, surveys, and health records—into actionable insights presented in reports, dashboards, and web applications. 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, machine learning, and natural language processing to turn complex datasets into predictive insights. To deliver these insights to stakeholders, I build and publish interactive data products using Quarto and Shiny, maintaining deployment workflows through GitHub and GitLab CI/CD pipelines and containers.

Outside of data science, I have a deep appreciation for nature and spirituality. From paragliding to yoga, I find energy and balance through exploring outer and inner landscapes.