Standard Bank Group is a leading Africa-focused financial services group, and an innovative player on the global stage, that offers a variety of career-enhancing opportunities – plus the chance to work alongside some of the sector’s most talented, motivated professionals. Our clients range from individuals, to businesses of all sizes, high net worth families and large multinational corporates and institutions. We’re passionate about creating growth in Africa. Bringing true, meaningful value to our clients and the communities we serve and creating a real sense of purpose for you.

As a Risk Analytics Engineer, you are the critical bridge between advanced analytics and our production environment. You will be embedded within a cross-functional squad, responsible for the operationalization of risk models and strategies. Your primary mission is to ensure that the analytical solutions built by our data scientists and risk analysts—from credit scorecards to real-time fraud models—are deployed, monitored, and managed in a robust, automated, and scalable fashion. You will build and own the MLOps pipelines and solutions that bring our risk intelligence to life.

Qualification: 

• Completed Matric
• Bachelor’s degree in Computer Science, Software Engineering, Information Systems, or a related quantitative field.

Experience Required

• 5-7 years experience in building databases, warehouses, reporting and data integration solutions.
• Experience building and optimising big data data-pipelines, architectures and data sets. Experience in creating and integrating APIs.
• Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement
• 8-10 years deep understanding of data pipelining and performance optimisation, data principles, how data fits in an organisation, including customers, products and transactional information. Knowledge of integration patterns, styles, protocols and systems theory
• 8-10 years experience in database programming languages including SQL, PL/SQL, SPARK and or appropriate data tooling. Experience with data pipeline and workflow management tools

Behavioural Competencies:

• Adopting Practical Approaches
• Articulating Information
• Checking Things
• Examining Information
• Interpreting Data
• Managing Tasks
• Producing Output

Technical Competencies:

• Big Data Frameworks and Tools
• Data Engineering
• Data Integrity
• Data Quality
• IT Knowledge
• Stakeholder Management (IT)