Absa Group Limited is a financial services conglomerate based in Johannesburg, South Africa, and is one of Africa’s largest diversified financial services groups. The company is publicly listed on the Johannesburg Stock Exchange (JSE) and has a presence in 12 countries across Africa. The company offers a range of retail, business, corporate, and investment banking products and services.

Job Summary

• The role will be responsible for building and operationalising machine learning and AI models, the Head: Data Science drives experimentation and innovation across telematics, risk modelling, and customer decisioning (including customer segmentation and client lifetime value).
• The role positions Absa Insurance at the forefront of digital insurance innovation and is explicitly distinct from Management Information and reporting functions. Master’s level in Data Science, Statistics, Mathematics, Computer Science, Engineering.

Job Description

• The role will be responsible for building and operationalising machine learning and AI models, the Head: Data Science drives experimentation and innovation across telematics, risk modelling, and customer decisioning (including customer segmentation and client lifetime value).
• The role positions Absa Insurance at the forefront of digital insurance innovation and is explicitly distinct from Management Information and reporting functions.

Telematics

• Build driver behaviour models that predict risk and reward safe driving.
• Use connected-device data (e.g., vehicle sensors, IoT geysers) to enable proactive risk management.
• Translate raw telematics data into underwriting insights and customer value propositions.

Risk Modelling

• Predictive Underwriting: Apply AI/ML to assess claim probability upfront (telematics, geospatial risk, external data) to sharpen risk selection.
• Portfolio Stress Signals: Monitor book performance with models for lapse/NTU risk, persistency, and concentration exposures, providing early warning to complement actuarial reserving.

Customer Decisioning

• Develop models for customer segmentation, targeting, and personalised offers.
• Predict client lifetime value (CLV) to optimise acquisition and retention investments.
• Support decision engines for next-best action, pricing, and cross-sell in digital channels.

Education

• Bachelor`s Degrees and Advanced Diplomas: Physical, Mathematical, Computer and Life Sciences (Required), Master’s Degree: Data Science (Required), Masters Degrees (coursework and research): Computer and Information Science (Required), Masters Degrees (coursework and research): Mathematics (Required), Masters Degrees (coursework and research): Statistics (Required)