Machine Learning Engineer at Capitec Bank

Purpose Statement

• To enable Data Scientists and Decision Scientists to do work more efficiently; build, implement, improve and support platform improvements which will support delivery of the Capitec AI strategy.
• To collaborate in creating and delivering the AI strategy to ensure Capitec is able to compete in a fast-changing landscape. The effective use of AI technologies will be a key strategic differentiator in the future.

Experience

NB: Length of experience for Machine Learning Engineers is conditional on the qualifications obtained

• Machine learning and software development experience
• Delivering nonstandard predictive models into a production environment 
• Working with Python and SQL
• Experience with the modern software development best practices, 
• Working in cloud environments.
• Experience with big data processing frameworks

Qualifications (Minimum)

• Masters Degree in Information Technology - Computer Science or Engineering - Other

Qualifications (Ideal or Preferred)

Knowledge

• Machine learning model life cycle
• Knowledge of machine learning patterns and concepts
• Understanding of distributed systems
• Understand a broad range of data structures and algorithms, and which to use
• Knowledge of engineering and operational excellence best practices
• Ability to debug code through common troubleshooting techniques such as metrics, logs and traces
• Predictive modelling techniques (statistical and machine learning) and deployment

Skills

• Analytical Skills
• Decision making skills
• Planning, organising and coordination skills
• Problem solving skills
• Researching skills