Data Scientist & ML Engineer
I spent nearly two decades solving complex problems in technical environments — from live audio engineering to designing enterprise AV systems for 11,000+ users at MillerKnoll. Somewhere along the way, I realized the most interesting problems were the ones hiding in data.
That realization launched a full pivot: a B.S. in Computer Science, an M.S. in Data Science & Analytics (both at Grand Valley State), and a growing portfolio of machine learning, deep learning, and statistical modeling projects that have earned multiple first-place finishes in Kaggle competitions.
Now I'm on MillerKnoll's Lean AI team — a small, high-impact unit leading the company's AI/ML transformation. I build Narrow AI tools that slot directly into business workflows, ship predictive models that inform real decisions, and help drive agentic AI adoption across the org. Same intensity and precision I developed managing mission-critical live events — just pointed at a very different stage.
Audio → Tech → Data Science
Career Pivot
2× First Place
Kaggle Wins
19+
Years in Tech
Lean AI @ MillerKnoll
Current Focus
MillerKnoll — Lean AI — Holland, MI
Wine-AI Startup — Holland, MI
MillerKnoll — Holland, MI
Grand Valley State University — Allendale, MI
MillerKnoll — Holland, MI
Grand Valley State University — Allendale, MI
Various Employers — Multiple Locations
Most Outstanding Graduate — Data Science & Analytics M.S. Program
College of Computing, Grand Valley State University · 3.5+ GPA
kNN Recommender System (Birds)
Neural Network CITE (ADT Prediction)
Cross-Modal VAE (Biological Prediction)
Wine AI Transformer (Tasting Notes)
Time Series — MillerKnoll DFA
Global Collaboration — MillerKnoll
Every model starts with the data. Exploratory analysis, assumption checking, and proper validation aren't optional — they're the foundation everything else is built on.
A beautiful model that lives in a notebook isn't a solution. I prioritize clean, deployable code — from prototype to production pipeline — because insights don't matter if nobody can use them.
The best analysis in the world is useless if stakeholders can't understand it. I translate complex results into clear, actionable recommendations for technical and non-technical audiences alike.
First results are rarely final results. I treat every project as an iterative process — exploring, refining, benchmarking, and improving until the solution genuinely fits the problem.