The ideal candidate should be comfortable spending most of their time working directly with data, features, models, scoring logic, validation methods, production workflows, and model improvement and should bring solid engineering judgment, ownership of their deliverables, and the ability to drive their work forward without waiting for perfect requirements. Because this role supports scores and decisioning systems, we value candidates who have built models that people can understand, trust, monitor, and act on scorecards, risk scores, health scores, calibrated models, score bands, thresholds, and business-facing model explanations.