Quantitative (Quant) Engineer

We are seeking highly analytical, data-driven Quantitative Engineers with strong statistical and modelling skills to build and deploy advanced risk models. You will work with large datasets, apply statistical and stochastic techniques, and collaborate across teams to deliver robust risk-modelling solutions. Project overview: The organisation is driving a major transformation of Clint onboarding andamp; Portfolio monitoring, focusing on automation, AI-driven decisioning, and reimagined end-to-end client journeys. The initiative aims to redesign how clients are onboarded, approved, contracted, activated, and continuously monitored for risk and opportunities. Core priorities include reducing Time to Yes, accelerating contract completion, enabling faster Ready to Transact processes, and improving post-onboarding monitoring. Quantitative Engineers and full-stack engineering teams will build a unified model to enhance onboarding intelligence and ongoing portfolio risk assessment. Key Responsibilities Model Development andamp; Validation Build, validate, and back-test predictive models for: Credit risk, Payment''s risk and transaction behaviour Anti-financial crime (AFC) indicators External market or event-triggered risks Develop statistical models that reliably capture portfolio risk exposures. Assess predictive power, performance metrics, and robustness of models using historical and stress-scenario data.Work with large datasets to detect patterns, identify ..... full job details .....