I am a Credit Risk Modeller focused on bridging advanced analytics with operational excellence in financial services. My work combines human-centred AI, ML, and data engineering practices to design, validate, and deploy credit risk models that improve decision-making, resilience, and customer outcomes. Currently, I apply these capabilities in the banking sector while conducting research in Lean Service 5.0 and Industry 5.0, exploring how AI, IoT, and intelligent automation can streamline end-to-end credit journeys and governance. Academically, I am an M.Sc. researcher in Production Engineering (Strategy and Systems Management), investigating how Lean Service 5.0 principles can raise the quality, speed, and reliability of risk decisions without compromising compliance or fairness. My interests include model lifecycle management, monitoring and drift, explainability, bias mitigation, and the interface between convergent regulation and AI-enabled risk. Professionally, I have experience building and innovating ML models for retail credit, collaborating with cross-functional teams (risk, product, data, and engineering) to move prototypes into production with measurable business impact. I enjoy translating complex methods into clear narratives for executives and regulators, and partnering with academia to validate methods and publish applied research.