Senior Quantitative Analyst

Description:

This role is central to shaping and governing advanced credit decisioning, behavioural, and collections models across personal loans and overdrafts. The successful candidate will play a key role in strengthening portfolio performance, managing risk, and driving sustainable growth through sophisticated analytics.

The primary purpose of this role is to design, implement, and continuously enhance best-practice credit, behavioural, and assessment models in line with regulatory requirements. This will enable effective risk management, improved customer outcomes, and the achievement of strategic objectives within Personal Banking.

Key Responsibilities:

• Design and optimise credit decisioning strategies that effectively balance portfolio growth with risk appetite across personal loan and overdraft products
• Drive portfolio performance by analysing and improving key ROE drivers, including NII, NIR, impairments, and underlying cost structures
• Identify innovative yet compliant opportunities within the National Credit Act (NCA) to enhance credit strategies and customer value propositions
• Apply advanced analytics and bureau data to build robust, efficient, and scalable decisioning models
• Analyse the impact of loan sizes and terms on take-up, risk, and profitability, to inform credit policy and risk appetite decisions
• Lead, coach, and develop a small team of Analysts to deliver against KPIs and strategic objectives
  Job Experience and Skills Required:
  
  • Education:
  • Bachelors degree in Data Science, Statistics, Actuarial Science, Mathematics, Computer Science, or a related field
• Masters degree preferred

Experience: 5+ years experience in quantitative or analytical roles within the unsecured credit environment Proven experience working on personal loan and overdraft portfolios within a major South African bank Strong track record in credit risk decisioning, including scorecards, credit policies, profitability models, and impairments Hands-on experience applying and interpreting the National Credit Act (NCA) in a credit decisioning context Demonstrated ability to translate complex data into clear and commercially sound insights Experience leading, mentoring, or managing Analysts (minimum 2 direct reports) Skills: Advanced proficiency in SQL and Python for data analysis and model development Strong working knowledge of Microsoft Office, particularly Excel Excellent quantitative, analytical, and problem-solving skills Strong business acumen with an understanding of ROE drivers and portfolio economics Effective stakeholder engagement and communication skills Ability to operate in a regulated, fast-paced, and data-intensive environment
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