Date: 6 Aug 2025
Location: Sandton, GT, ZA
Company: Capitec Bank Ltd
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We're on the lookout for energetic, self-motivated individuals who share our passion for service in the banking industry. To be part of the journey, follow the steps below:
- To see what life at Capitec is all about and complete a short assessment, please click here!
- Once you have completed the above finalize your application by clicking apply below
- To Lead a Decision Science team, prioritising and overseeing analysis to translate active business data into usable strategic information which informs the business regarding critical and measurable Credit and risk indicators.
- To ensure that the delivery within the area of responsibility aligns with the objectives, plans, processes, and standards of Decision Science.
- Honours Degree in Mathematics or Statistics
- Grade 12 National Certificate / Vocational
- Masters Degree in Mathematics or Statistics
Minimum Experience:
- Over 6 years proven work experience in an analytical science role (of which, at least 3 years' experience in a Leadership or Management role requiring validating work)
- Extracting and aggregating data from large relational databases
- Data mining and predictive modelling
- Programming (SAS, SQL, R, Python)
- Developing scorecards from scratch
- Stakeholder relationship engagement and management
- Responsibility for delivery in a fast-moving environment
- Advanced analytics
- Interpretation of user requirements and translation into business requirements specifications (business analysis requirements gathering)
- Business acumen to identify the impact technical issues may have on design and delivery of solutions
- People management practices and principles
- Project management methodologies
- IT implementation cycle
- Credit cycle
- Best practices for Decision Science (such as reusability, reproducibility, continuous monitoring, etc.)
- Deep technical understanding of state of the art statistical (predictive and classification) model development and deployment principles and techniques including traditional Scoring (logistic regression with binning and missing value replacement (e.g., reject inference), Machine Learning (neural networks, SVM, random forests, etc.), and Quantitative Analysis (time value of money, etc.) - and able teach to a broad technical audience
- Underlying theory / principles and application of Machine Learning models / language
- Banking / Financial sector
- Credit environment / industry
- Numerical Reasoning skills
- Analytical Skills
- Problem solving skills
- Decision making skills
- Researching skills
- Presentation Skills
- Facilitation Skills
- Planning, organising and coordination skills
- Attention to Detail
- Communications Skills
- Interpersonal & Relationship management Skills
- Leadership Skills
- Clear criminal and credit record
Apply now
