Building enterprise forecasting platforms
Forecasting is not only a model. It is a decision system that has to keep product, inventory, price, promotion, supplier, and location data aligned.
Engineering
Problems, not employer names.
These case studies describe the engineering patterns that shaped my work. They are deliberately public-safe and focus on decisions, tradeoffs, and lessons rather than proprietary implementation details.
Modernizing analytical platforms without losing meaning
Cloud migration changes infrastructure quickly. Business definitions and operational confidence move more slowly.
Keeping data trustworthy when systems disagree
Validation catches malformed data. Reconciliation deals with records that are valid and still cannot all be true.
Observability that follows evidence, not only infrastructure
Logs and metrics describe system behavior. Investigations also need to know whether the evidence itself is complete and reliable.
Making AI dependable before model evaluation
AI reliability begins with the data path, ownership, context, and controls around the model—not only the model score.