Jeff Goseland
ML Engineer building intelligent systems at scale
Principal ML Engineer | Music Cognition Research
Twenty years at Walmart in replenishment and supply chain: technical lead on Global Replenishment System, architect of Event Driven Fulfillment and Order Well, and later Principal roles designing MILP-based inventory placement and safety stock optimization. Led teams of up to 24, delivered cloud-native systems at scale (13B daily transactions), with documented supply chain impact approaching $900M.
MS in Data Science, University of Notre Dame (May 2026). Capstone at Acorns: production LightGBM winback modeling on Databricks with MLflow and SHAP. Research direction: music cognition and emotion modeling, bridging optimization rigor with interpretable, human-centered ML. Also building NoeticIQ. See Education for academic background.
Research Interests
- Music cognition: emotional trajectory, arousal/valence, Tonnetz geometry
- Optimization: MILP, integer programming, constraint design
- Human-centered AI systems with interpretable interfaces
Exploring PhD paths in music cognition plus optimization: ML/CS with a music focus, or music informatics with an optimization angle. Preference for local/part-time, remote funded international, or selective full-time programs.
All models are approximations. Usefulness beats precision. Interpretability matters in human-centered domains.