Team Leader: Data and Analytics at Capitec Bank

About the role:

• As a Lead Data Scientist (Retail Credit), your purpose is to own and advance Capitec’s highest materiality client exposure models, the intelligence that identifies salary deposits with near perfect precision and drives credit eligibility and downstream treatments in both batch and real time (branch side) pathways. You’ll combine deep research with production pragmatism to evolve our sequence-type deep learning neural network models, ensuring they remain accurate, explainable, and robust under heavy load and tight SLAs. You’ll shape the analytics behind our enterprise “10 minute flow” (3 screen journey), turning complex data into simple, trusted decisions for clients and bankers alike.
• The role spans the full ML and Data Science lifecycles and the people leadership required to execute it well. You will lead a squad of Data Scientists, stewarding model design, feature governance, Model Risk Management grade documentation, approvals, deployment, and continuous monitoring. You’ll partner daily with RCED, delivery teams, and Branch Ops, to keep batch runs and real time scoring healthy, documented, and continually improved. With recent platform migrations, you’ll guide the team as deployments are detangled from platform engineering and stabilised as services the squad fully owns, freeing focus for pay date intelligence, collections strategies, and a client level view that compounds value over time.

Our ideal candidate has:

• 7+ years building and running high stakes ML models in production (financial services or adjacent), with clear impact on credit exposure or client treatment.
• Demonstrable mastery of sequence-type deep learning neural networks; comfortable balancing accuracy, explainability, and control.
• Hands on ownership of batch and real time scoring.
• Fluency in Python/SQL, model packaging and service exposure; experience with AWS (SageMaker, Kubernetes, or equivalent cloud), Git/GitHub, and collaborative documentation (Confluence).
• Proven leadership of 4–5 DS/MLEs, establishing code/review standards, mentoring, and elevating research & engineering practice.
• Stakeholder management across RCED, Delivery, Branch Ops, and governance forums.
• Model Risk Management mindset: rigorous documentation, approval pathways, monitoring and retraining.
• Have the ability to articulate where and why a model is used, what happens if it drifts and what the risk to clients and the Bank are

Ideal:

• Experience with pay date models, Next Best Action, or collections; prior exposure to Documents Exchange (multi bank statements) and strategies for timely retraining when external data shifts.

Competencies:

• Strategic thinking
• Leadership ability
• Problem solving skills
• Decision making skills
• Researching skills
• Project Management skills
• Planning, organising and coordination skills

Education:

• Completed a master’s degree or higher

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