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Belonging at Absa

Absa is committed to creating an inclusive workplace where everyone can thrive. We are an equal opportunity employer and welcome applications from suitably qualified individuals from diverse backgrounds. In support of our Diversity, Equity, Inclusion and Belonging (DEIB) commitments and Employment Equity objectives, preference may be given to candidates from underrepresented designated groups, including persons with disabilities. We encourage applicants who may require reasonable accommodation during the recruitment process to let us know so that appropriate support can be provided.

Job Summary

Job Description

Quantitative Analysis and Modelling:

• Develop and maintain Treasury forecasting, optimisation and behavioural models supporting pricing, balance sheet planning, liquidity risk and interest rate risk analytics. Build statistical forecasting frameworks for cashflows and funding profiles under multiple rate scenarios. Design optimisation models to improve funding mix and balance sheet outcomes within regulatory and risk constraints. Implement behavioural models for deposits and lending products, including prepayment, decay and repricing dynamics, using data-driven calibration and back-testing.

Risk and Regulatory Analytics:

• Implement quantitative solutions to measure and monitor liquidity metrics, funding stability and interest rate sensitivity. Support production of regulatory measures through model 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 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.

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.

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:
  • Forecasting
  • Classification
  • Optimisation
  • Statistics, probability theory
  • Data analysis

• Programming Proficiency: Proficiency in programming languages such as SAS, Python, R, MATLAB, or similar languages. Experience in data manipulation, statistical analysis, and numerical computation using these languages. Familiarity with database querying languages (e.g., SQL) is a plus.
• 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.

Bonus Competencies:

• A good understanding of econometrics
• Regulatory Awareness: Familiarity with regulatory requirements related to financial modeling in banking, such as Basel III, IFRS 9, and stress testing frameworks. Understanding of risk management concepts and regulatory compliance within the banking industry.
• Financial Market Knowledge: Strong understanding of financial markets, instruments, and products, particularly those related to banking Treasury activities. Knowledge of interest rate derivatives, fixed income securities, liquidity management, and risk measurement methodologies is highly desirable.

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, liquidity or interest rate risk.
• Practical programming experience in Python and SAS, including building production-ready analytical tools and automated data processes.

Education