(1731) Data Scientist and AI Engineer - BSTD at South African Reserve Bank

Detailed description

The successful candidate will be responsible for the following key performance areas:

• Translate business problems into technical solutions, including data science models, software implications and scalability.
• Design and develop scalable AI/ML models based on business requirements.
• Verify the accuracy of incoming data by validating its sources and maintaining regular communication with data providers.
• Conduct experiments, including AI model research and development, evaluate algorithms and build prototypes. 
• Implement robust processes to ensure the ongoing quality and reliability of data used in analytics and reporting. 
• Build and maintain data pipelines for training and inference.
• Analyse large datasets to extract meaningful insights and features.
• Develop appropriate ML model performance metrics.
• Monitor and retrain models based on feedback and data drift.
• Conduct research and implement state-of-the-art algorithms and tools to identify advanced analytics trends in peer organisations and similar industries, and use these insights to support benchmarking activities, particularly for specific risk types, ensuring that practices remain competitive and aligned with industry standards.
• Deploy AI models to production using application programming interfaces (APIs), containers or cloud platforms.
• Stay abreast of legislative changes and developments in advanced analytics, and proactively suggest how these developments can be leveraged to enhance current practices and drive continuous improvement.

Job requirements

To be considered for this position, candidates must be in possession of:

• a Bachelor’s degree in a mathematical science such as Statistics, Actuarial Science, Economics, Applied Mathematics, Informatics, Computer Science or a related analytical field, or an equivalent qualification;
• at least five to seven years’ experience in the field of data science or relevant analytics environment;
• financial sector experience (would be a strong advantage); and
• relevant data analytics (would be an added advantage).