The mission Build a state-of-the-art ML platform and the discipline around it. Models with a price tag. Every model has a business case and a measurable monetary outcome. Credit and decisioning models built with rigorous validation, champion/challenger testing and explainability. A production ML platform. Serving, monitoring, reproducibility and retraining are engineered, not improvised. Responsible AI, built in. Model risk, bias and explainability checks, with an independent sign-off gate before anything reaches production. Agent-first systems. Agents are production components with orchestration, guardrails, evals and observability. ◆ Models on governed data. You build on a point-in-time-correct feature store, not around it. This is a business function. Every model carries monetary value, and you will run the function that way: compute budget, headcount and return on investment.