Company Description
Standard Bank Group is a leading Africa-focused financial services group, and an innovative player on the global stage, that offers a variety of career-enhancing opportunities - plus the chance to work alongside some of the sector's most talented, motivated professionals. Our clients range from individuals, to businesses of all sizes, high net worth families and large multinational corporates and institutions. We're passionate about creating growth in Africa. Bringing true, meaningful value to our clients and the communities we serve and creating a real sense of purpose for you.
To manage the optimal development, deployment, maintenance, and monitoring of high-quality credit risk models throughout the credit life cycle, upholding model governance standards. Apply innovative machine learning techniques, conduct customer-centric data analytics, and contribute to dashboard creation.
Qualifications
Type of Qualification: First Degree
Field of Study: Mathematical Sciences, Risk Management, Analytics, Quantitative Studies
Experience Required
Credit Risk - BCB
Risk & Corporate Affairs
8-10 years
Be able to identify and implement process improvements in model development, deployment, and monitoring workflows within banking environments.
8-10 years
Develop monitoring dashboards and effectively communicating analytical insights and KPIs to stakeholders. Ensuring adherence to model risk management and governance standards, ensuring compliance with regulations and internal governance requirements specific to credit risk models. Strong communication skills, particularly in translating technical modelling concepts into actionable insights for non-technical stakeholders, supporting decision-making.
8-10 years
Experience in credit risk modelling, including development, enhancement, deployment, and monitoring of credit risk models across the credit life cycle and various portfolios. Experienced in the application of machine learning techniques specifically for credit risk modelling, enhancing predictive modelling accuracy. Experience and knowledge of client-centric data analytics, interpreting complex data sets for credit risk assessment, and leveraging alternative data sources.
Additional Information
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