Head Modelling & Analytics at Absa Group Limited (Absa)

End Date: May 13, 2026

Quantitative Analysis and Modelling:

• Develop/optimise and maintain Treasury cash flow engine and EUDAs to ensure accurate reporting, forecasting, and behavioural assumptions supporting funding and liquidity risk and depositor insurance reporting.

Risk and Regulatory Analytics:

• Implement quantitative solutions to measure and monitor liquidity metrics and funding stability. Support production of regulatory measures through model/EUDA development, data analysis and automation of calculation processes. Conduct stress testing and scenario modelling to assess the impact of market movements and balance sheet changes.

Data Engineering and Automation:

• Extract, transform and analyse large Treasury datasets to support modelling and reporting requirements. Build scalable, well-documented code and automated pipelines to improve model efficiency, reproducibility and governance. Enhance existing tools through optimisation, refactoring and improved data validation controls.

Model Governance, controls and Validation Support:

• Produce clear technical documentation covering model methodology, assumptions and limitations. Assist with model validation exercises, benchmarking, remediation actions and audit queries. Ensure development practices align with internal model risk standards and regulatory expectations.
• BCBS 239 / RDARR compliance: defining, maintaining and creating controls and processes ensuring compliance with control standards.

Stakeholder Collaboration:

• Work closely with ALM, Funding, Risk and Finance teams to translate business requirements into quantitative solutions. Provide technical explanations of model outputs and assumptions to both quantitative and non-technical stakeholders.

People Management and Leadership

• Develop, manage and support internal capability of a sustainable high performing team who will ensure the necessary resources are in place to achieve business strategy and objectives; while encouraging professional growth.
• Motivate team members through coaching and mentoring them to perform optimally around the vision and values, create a sense of urgency and excitement around the business and ensure that they strive to deliver optimally.

Continuous Improvement and Technical Innovation:

• Stay current with industry developments in Treasury modelling, balance sheet analytics and financial risk measurement. Proactively identify opportunities to enhance modelling approaches, improve computational performance and strengthen analytical capabilities.

Required Skills:

Crucial skillset: A strong statistical modelling/ data science background preferably with model development experience in the area of:

• ALM
• Forecasting
• Classification
• Optimisation
• Statistics, probability theory
• Data analysis
• Programming Proficiency: Proficiency in programming languages such as Python and SAS. Experience in data manipulation, statistical analysis, and numerical computation. Familiarity with database querying languages (e.g., SQL) is a plus.
• Analytical/data visualisation Proficiency: Power BI and Qlikview / QlikSense experience.
• Communication and Collaboration: Excellent verbal and written communication skills with the ability to explain complex quantitative concepts to both technical and non-technical stakeholders. Demonstrated ability to collaborate effectively with cross-functional teams and present findings in a clear and concise manner.

Qualification

• Bachelor’s or Honours degree in Quantitative Analytics, Financial Engineering, Mathematics, Statistics, Actuarial Science, Computer/ Data Science or a related quantitative or model development discipline.

Experience

• 3–5 years’ experience in quantitative modelling, Model Development or Treasury / ALM within a banking or financial services environment.
• Proven experience developing or maintaining forecasting, optimisation or behavioural models, preferably related to balance sheet management, and liquidity risk.
• Practical programming experience in Python and SAS, including building production-ready analytical tools and automated data processes.
• Power BI and Qlikview / QlikSense experience

Education

• Bachelor`s Degrees and Advanced Diploma: Business, Commerce and management Studies (Required)