Senior Engineer, Risk Analytics Solutions

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 Solution Engineer, you are the critical bridge between advanced analytics and our operational environment. You will be embedded within a cross-functional squad, responsible for the operationalization of AI, 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 orchestration solutions within AWS to support our Risk Solutions which includes SAS Viya, and AWS Services that bring our risk intelligence to life.

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

Experience

• 3-5 years' experience in the relevant technical role such as DevOps Engineer, MLOps Engineer, Cloud Engineer or Data Engineer with focus on automation.
• Strong programming proficiency, particularly in Python.
• Proven experience with CI/CD tools (e.g. GitLab actions, Azure DevOps, Jenkins)
• Hands-on experience with cloud platforms (AWS or Azure)
• Experience with containerisation technologies and distributed computing (Docker, Kubernetes)
• Familiarity with Infrastructure as Code (IaC) tools (Terraform, Cloud Formation)
  
   

Behavioural Competencies:

• Adopting Practical Approaches
• Articulating Information
• Developing Expertise
• Documenting Facts
• Embracing Change

Technical Competencies:

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