• Lead the definition and evolution of risk frameworks across the customer lifecycle, with a focus on early-stage and onboarding risk. • Design, develop, and own core fraud and risk metrics that inform decision-making, performance measurement, and strategy. • Partner with internal stakeholders (Product, Engineering, Risk Operations) to translate analytical insights into scalable solutions. • Evaluate, integrate, and manage external data sources to enhance risk detection and decisioning capabilities. • Define data requirements and partner with engineering to build and maintain reliable, production-grade data pipelines. • Act as a thought leader in fraud analytics, setting best practices for measurement & risk modelling.