Ryan Wolbeck
Head Of AI And MLOps Platform
Jordan, Minnesota, United States
Summary
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Rockstar🎓
Top SchoolRyan Wolbeck is a Head of AI and MLOps Platform with seven years of applied data science and operations leadership experience, currently scaling AI-driven manufacturing and supply chain solutions at Kraft Heinz. He combines an academic foundation in applied economics with hands-on expertise in computer vision, predictive analytics, and generative AI to drive measurable improvements in production, transportation, and inventory efficiency. Ryan has a track record of leading cross-functional teams to deploy production-grade ML systems—often bridging data engineering (Python, Docker, FastAPI) with business strategy for clear ROI. An active open-source maintainer, he contributes to the widely used NGBoost project, adding practical model-tuning examples and improving reproducibility for probabilistic prediction. Based in Jordan, Minnesota, he blends domain-specific operational know-how with platform-level MLOps thinking to accelerate model-to-production lifecycles.
7 years of coding experience
8 years of employment as a software developer
Master of Science (M.Sc.) Applied Economics, Master of Science (M.Sc.) Applied Economics at University of North Dakota
English, Spanish
Github Skills (10)
hyperparameter-optimization10
jupyter-notebook10
machine-learning10
python10
gradient-boosting10
scikit-learn9
estimate9
scikit9
uncertainty9
hyperopt8
Programming languages (3)
Github contributions (5)
stanfordmlgroup/ngboost
Jul 2020 - Jan 2023
Natural Gradient Boosting for Probabilistic Prediction
Role in this project:
Data Scientist & ML Engineer
Data Scientist & ML EngineerContributions:25 releases, 44 reviews, 63 commits in 2 years 6 months
Contributions summary:Ryan contributed significantly to the project by adding and modifying example notebooks for hyperparameter tuning using Hyperopt with NGBoost. They added a new notebook example, added evaluation on the test set. They also updated the version and applied black to format the files. Their work demonstrates an understanding of machine learning model optimization and experimentation within the context of probabilistic prediction, as described by the repository's description.
pythonpredictionnaive-bayesnatural-gradientsmachine-learning
ryan-wolbeck/ngboost-tuner
Jul 2020 - Aug 2020
A CLI Tuner of NGBoost
Contributions:2 releases, 3 PRs, 30 pushes in 1 month
tunerngboostcli
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