• Completed SAICA / SAIPA Articles
• 0 to 2 years post articles working experience of Financial Accounting
• This should include the responsibility for executing a wide range of accounting functions
• Providing financial advisory support to Business

• 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

• 6+ years of experience in a Senior Data Science role
• Bachelor’s degree or higher.
• Hands-on experience deploying AI/ML solutions in real-world applications
• Experience with advanced data science principles including NLP, deep learning, reinforcement learning, or time-series modeling.
• Python/R experience and relation/non-relational databases.
• Familiarity with modern deep learning frameworks (Pytorch, Tensorflow)
• Stakeholder engagement management up to executive management.
• Github experience or Git
• AWS/Azure/GCP

• Completed a degree or higher

•          Sales and sales optimisation techniques & principles

•          Commercial/business know how (how businesses work.)

•          Client relationship management principles

•          Engagement/conflict management practices

•          Performance culture

• The features, benefits and value propositions of respective company product/service offerings.
• General banking practices and procedures.
• Understanding of how Business Banking operates, as well as understanding the business risks, industry risks and financial requirements pertaining to the business market
• Credit principles and practices, including an understanding of credit application, securities and balance sheet requirements. .
• The Financial Intelligence Centre Act (FICA).
• Administration processes and procedures pertaining to Business Banking transactions.
• Client relationship management and service principles.

• 4 – 6 years’ experience in retail credit analysis (including programming in SQL / SAS / R / Python, descriptive and diagnostic analytics, statistical modelling, and data visualisation).
• In case of Honours degree: 3 – 5 years’ experience in retail credit analysis (including SQL programming and descriptive analytics).
• Credit intelligence performance and optimisation.

• Experience in data engineering or a related field.
• Proficiency in SQL, Python, and version control tools (e.g., Git).
• Experience with cloud platforms (e.g., AWS) and cloud-native data architecture.
• Ability to design and manage data pipelines and data models.
• Experience working with large datasets in structured data warehouse environments.
• Familiarity with ETL processes and data transformation best practices

• Functional knowledge according to the portfolio; design techniques and methodologies
• The advertising and creative process
• Ideation and prototyping
• Visual communication design for Corporate environments
• Internal communication and business processes
• Microsoft Office (MS Word, MS Excel, MS Outlook)
• Industry-standard design software (Adobe Cloud, Figma, Sketch, InVision)
• Time and workload management
• Data-driven marketing
• Digital marketing and marketing technology

• At least 4-5 years’ experience in a Financial Crimes Operations environment, dealing with detection and response within a banking / financial services organisation
• At least 3 years’ experience in leading a team
• Experience in Fraud Risk Management within a fast-paced and complex business setting
• Exposure to banking and risk systems
• Comprehensive understanding of the South African financial/banking environment
• Contribute and be accountable to relevant legislation pertaining to fraud and banking.
• Understanding of customer care and service protocols
• Familiarity of common fraud typologies and emerging trends in fraud and financial crime

• 4 – 6 years’ experience in retail credit analysis (including programming in SQL / SAS / R / Python, descriptive and diagnostic analytics, statistical modelling, and data visualisation).
• In case of Honours degree: 3 – 5 years’ experience in retail credit analysis (including SQL programming and descriptive analytics).
• Credit intelligence performance and optimisation

2-4 years’ experience in retail credit analysis (including SQL programming, diagnostic analytics, statistical modelling and data visualisation).
In case of Honours degree: 1 – 3 years’ experience in retail credit analysis (including SQL programming and descriptive analytics).
Ideal:

Portfolio specific experience
Capitec Bank experience
Qualifications (Minimum)
Bachelor’s Degree in Finance or Statistics