Head: Decision Science

Purpose Statement

• To provide Credit Decision Science insight and input to either the Retail Bank or Business Bank Credit strategy which aligns with the organisational strategy and which provides strategic analysis and translates active business data into usable strategic information to inform business on credit decisions and risk.
• To translate the strategy into business plans and objectives and implement through leading, managing and providing direction to a team of specialists within the Credit Decision Science function.
   

Experience

Minimum:

• 10 years credit risk analytics environment experience and 
• 5 years management experience including;
  • Leadership / management of people 
  • Investigation, analysis, design and delivery of business solutions
  • Data mining and predictive modelling
• Proven experience of using influence and relationships to drive and achieve objectives. 
• Experience of successfully leading, planning and managing Credit Decision Science initiatives across a large organisation

Ideal:

• Management experience in Capitec Bank.
• Experience in the same or a similar industry

Qualifications (Minimum)

Qualifications (Ideal or Preferred)

Knowledge

Minimum & Ideal:

• Knowledge and experience of the respective Retail or Business Bank Credit life cycle/value chain
• Expert knowledge of Credit Decision Science best practice, methods, tools, technology
• Commercial, business and financial principles and practices
• Building and developing effective teams
• Credit Decision Science management systems
• Best practices and tools in credit risk analytics
• Governance and risk management principles
• Business products, processes, policies and systems
• Data analysis, data management and data governance
• Quality principles and practice
• Project management methodologies and life cycle
• Design and delivery of business solutions
• Retail credit environment / industry
• Confidentiality and intellectual property implications and constraints
• Interpretation of user requirements 
• Translation of business requirements into business requirement specifications 
• HR management policies and practices
• People management skills and techniques
• Understanding of;
  • credit scoring and rules engine systems
  • data warehouse environments 
  • IT development cycle regards the deployment of credit products
  • the use of machine learning, artificial intelligence and cloud technology in the optimisation of credit risk analytics and products
  • the governance and controls required in the development and deployment of credit risk models from scorecard development to deployment into the IT systems and the tracking there of

Skills

Conditions of Employment