(1731) Data Scientist and AI Engineer - BSTD

Job Description Brief description The main purpose of this position is to design, develop, manage and implement artificial intelligence (AI)-driven solutions that leverage high-quality, well-governed data to create intelligent systems through machine learning (ML) and deep learning, to ensure that AI initiatives enhance automation, efficiency and decision-making while adhering to data and information management principles, governance frameworks and ethical AI standards.

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. Qualifications 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).

Additional requirements include: knowledge and skill in: industry, organisational and business awareness; continuous learning and/or professional development; quality assurance; information management; enterprise information management (EIM) strategy; data quality management; proficiency in data analytics or a general data analysis environment with application of statistical/machine learning techniques; familiarity with data manipulation tools (e.g.

SQL, Python, R, SPSS, Microsoft Excel, MATLAB, SSMS and SAS); experience with on-premise and/or cloud-based big data environments (e.g. HADOOP, SPARK, NoSQL, Microsoft Parallel Data Warehouse, Amazon Web Services (AWS) and Microsoft Azure); extensive experience with common RDBMS technologies (e.g. Oracle, IBM DB2, Microsoft SSMS and MySQL); ability to analyse and interpret complex data-driven problems and/or business processes that span multiple domains, identify and understand the requirements, and produce relevant visualisations; and ability to translate complex analytical concepts into clear, accessible language for business stakeholders.

In line with the SARB's commitment to diversifying its workforce, preference will be given to suitable candidates from designated groups. People with disabilities are welcome to apply. The SARB offers remuneration and benefits commensurate with the level of the position and in line with the market. The level at which the successful applicant will