Personal and Private Banking (PPB) AI/ML Engineer Graduate Programme needed at Standard Bank Group

You will learn to;

• Apply engineering and math skills to analyse and prepare structured/unstructured data for modelling, to support the Data Analysis and Engineering requirements of the role.
• Apply the most appropriate algorithms and/or build novel algorithms/techniques to fit the problem statement identified, which will support AI Modelling; take advantage of pre-built AI capabilities offered by Cloud vendors where appropriate to increase project velocity, take advantage of latest state-of-the-art commercialised AI solutions and reduce internal technical debt.
• Build and deploy new AI solutions for clients, according to client needs, to improve various business outcomes and drive innovation.
• Collaborate with subject matter experts to select the relevant sources of information and translate the business requirements into AI/ML outcomes. Present findings and observations to team for development of recommendations.
• Conduct research into and carry out AI and ML development processes to ensure the business unit fulfils the needs of AI and ML strategies.

Contribute to initiatives that include (But are not limited to);

• Driving improved Customer experience and retention through AI, to support a positive client impact.
• Driving growth and retention of customer revenue.
• Reducing annual operational costs of SBG through AI-powered automation.
• Pushing SBG towards transforming into a more AI-native organisation, supporting a positive shareholder impact.
• Contributing to the design and development of analytical AI and ML methods to support novel approaches of data and information

Qualifications

Final year undergraduate, Honours or Masters Degree (Completed or currently completing in 2025);

• Computer Science
• Artificial Intelligence and Machine Learning
• Electronic Engineering
• Mechanical Engineering
• Mechatronic Engineering
• Mathematics, Applied Mathematics
• Informatics, Information Systems
• Software Development
• Software Engineering
• Data Engineering
• Data Science
• Quantitative Risk Management