Quantitative Credit Analyst

About the role

The Group Credit Investment (GCI) Quantitative Credit Analyst is a quantitative specialist embedded in the Credit Team, responsible for developing, maintaining and enhancing internal credit rating scorecards. The role turns financial and non-financial risk drivers into practical, transparent scoring frameworks that support consistent credit assessment and monitoring across the GCI investment credit portfolio. It works closely with fundamental credit analysts, who keep the final credit judgement.

Key responsibilities

• Develop, maintain and enhance internal credit rating scorecards, including redevelopment where needed
• Identify risk drivers with credit analysts, evaluate variable selection, weightings, thresholds and rating mappings, and calibrate models where data permits
• Test scorecard performance, stability and consistency, run back-testing and benchmarking, and investigate rating migrations and anomalies
• Maintain clear methodology documentation and controlled, reproducible scorecard implementations with version control
• Prepare validation reports, support independent validation and address review findings
• Run scenario and sensitivity analyses, analyse financial statements and contribute quantitative analysis to credit papers and committee discussions
• Support consistent scorecard application through guidance, user support and knowledge sharing, and collaborate with the Analytics Function

Required profile

• Degree with substantial quantitative content (statistics, mathematics, econometrics, actuarial science, engineering, quantitative finance, business science or equivalent)
• 2-3 years of relevant experience
• Applied experience in quantitative modelling, statistical analysis and financial data, including testing assumptions and explaining model limitations
• Sound understanding of financial statements, credit risk, investments and fixed income instruments
• Advantageous: credit scorecard experience, postgraduate qualification, CFA or CA(SA)

Required skills

• Practical programming in Python, R or an equivalent language
• Strong Excel and financial modelling skills
• SQL, reproducible workflows and version control are advantageous