ABOUT ME
I’m a Data Scientist with over five years of experience building predictive models, forecasting systems, and production machine-learning pipelines across healthcare, education, and media.
I grew up in Southern Illinois and followed a nonlinear path into data science. This nonlinear approach shaped how I approach problems today. After beginning my studies in engineering, I transferred to Grinnell College, where I discovered the power of social science, statistics, and rigorous analytical thinking. I graduated with honors in Sociology with a concentration in Statistics, and later completed a professional certificate in Machine Learning & Artificial Intelligence through UC Berkeley.
Professionally, I specialize in owning the full lifecycle of data products: from data engineering and feature design to modeling, deployment, and monitoring. I enjoy working in complex, real-world environments where data is imperfect, assumptions must be tested, and solutions need to be both statistically sound and operationally practical.
I currently work as a Data Scientist at Inteleos, where I lead enterprise-wide forecasting and machine-learning initiatives, and I also consult on applied data science projects. I’m especially interested in building systems that replace ad-hoc decision-making with transparent, reproducible analytics.
TESTIMONIALS
"I had the pleasure of working with Denali while we both worked on the Data Science team at Solstice Studios. Denali is the type of person you hope to get as a teammate: a self-starter, intrepid, quick to learn new skills, open to feedback, stellar communications skills, and a solid background in both statistics and programming. While at Solstice, Denali worked on quite a few predictive analytic projects in RStudio that required knowledge of common machine learning methods (e.g., random forest models), R Shiny application development, and communicating model performance results to non-technical audiences. He also helped develop and implement a "fuzzy-matching" process in DBT/Snowflake that reconciled movie titles so data could be matched across multiple data sources. Quite simply, he's a great catch for any data science team, and both his technical and interpersonal skills are at a level well beyond his years."
"You may be familiar with the highly desirable "get it done" attitude, but what about an "it's already done" attitude? That's Denali in a nutshell. Proactive and lightning quick, he seems to have analytic tasks complete before I request them. On top of that, highly receptive to feedback, gracious, a tremendous collaborator, and a loyal employee. Denali is a rising star in the data science world."