Detailed description
The successful candidate will be responsible for the following key performance areas:
Take responsibility for business as usual (BAU) resource planning and management to ensure effective delivery and business continuity to balance demand and supply for work completed by various projects.
Establish and develop of AI integration strategies (strategic implementation) within the existing technology ecosystems.
Use data-driven insights (analyse complex datasets) to guide AI model development.
Lead the design and implementation of intelligent solutions using AI techniques such as machine learning, deep learning, natural language processing (NLP) or computer vision to create smart systems.
Work with data scientists, software developers, business analysts, product teams and business executives (cross-functional collaboration) to translate ambiguous business needs into clear, scoped and high-impact AI projects.
Authorise AI usage considering context of use to ensure fairness, explainability and privacy to address ethical concerns in AI systems.
Manage and coordinate the overall data science and AI maturity assessment within the SARB against best practices.
Drive the delivery of complex projects from conception to value-realisation.
Stay ahead of the curve on the latest advancements in AI/machine learning.
Proactively identify and propose new opportunities for applying these technologies to drive innovation.
Manage the performance and development of the data science and AI team.
Coordinate and manage the development of standards, frameworks, guidelines, processes and procedures across the data science and AI capability within the SARB.
Provide integrated reporting in relation to EIM operations, including but not limited to governance structures, projects, demand management and BAU.
Job requirements
To be considered for this position, candidates must be in possession of:
an Honour's degree (NQF 8) in Mathematical Sciences (i.e. Statistics, Actuarial, Economics, Informatics or Computer Science, Robotics, Applied Mathematics and Econometrics) or an equivalent qualification;
8−10 years' experience as a Data Scientist and AI Engineer; and
four years' experience in a supervisory role in Advanced Analytics/Data Science.
The following would be added advantage:
financial sector experience; and
relevant data analytics certification (e.g. Google AI, IBM AI Engineering or Deep Learning AI).