Snr Credit Risk Model Developer/Data Scientist

About the Role

We are seeking an experienced quantitative credit risk professional to lead the development, enhancement and governance of IFRS 9 impairment models. This role requires an individual who has hands-on experience developing Expected Credit Loss (ECL) models and successfully taking them through internal model governance, independent validation, internal audit and external audit processes. The successful candidate will combine deep technical modelling expertise with strong stakeholder management skills and the ability to translate complex analytical outcomes into commercially sound business decisions.

Key Responsibilities

• Development and redevelopment of IFRS 9 impairment models, including Probability of Default (PD), Loss Given Default (LGD), Exposure at Default (EAD) and Expected Credit Loss (ECL) methodologies.
• Own the end-to-end model development lifecycle, from data exploration and methodology design through implementation, validation support and production deployment.
• Drive model governance activities
• Address validation and audit findings, ensuring models meet regulatory and governance standards.
• Monitor model performance and recommend enhancements where appropriate.
• Work closely with Credit Risk, Finance, Collections, Data Engineering and Technology teams to ensure robust model implementation.
• Perform advanced statistical analysis using large and complex datasets.
• Build scalable analytical solutions using Python and SQL.
• Present technical findings to senior executives and governance committees.

Qualifications and Experience

Qualifications

• Honours degree in Statistics, Mathematics, Data Science, Actuarial Science, Quantitative Risk Management or another related quantitative discipline.
• A Master's degree in above fields will be advantageous.

Experience

• 5 or more years' experience in credit risk analytics or credit risk modelling.
• Proven experience developing IFRS 9 impairment models within a banking environment.
• Successfully implemented IFRS 9 models into production.
• Experience taking models through the complete governance lifecycle, including:
  • Independent Model Validation
  • Model Risk Committees
  • Internal Audit
  • External Audit
• Strong understanding of the end-to-end credit risk lifecycle, including acquisition, behavioural risk and collections.
• Experience working with large and complex datasets.
• Ability to translate analytical insights into practical business recommendations.

Technical Skills

• Advanced SQL programming.
• Strong Python programming skills.
• Candidates with extensive SAS experience and the ability to transition to Python are encouraged to apply.
• Strong statistical modelling and analytical capability.
• Experience with model monitoring and performance tracking.

Build a successful career with us

We are all about building strong, lasting relationships with our employees. We know that you have hopes for your future your career, your personal development and of achieving great things. We pride ourselves in helping  our employees to realise their worth. Through its business clusters Sanlam Personal Finance, Sanlam Emerging Markets, Sanlam Investments, Sanlam Corporate, Santam, Miway, as well as the Group Office the group provides many opportunities for growth and development.

Turnaround time

The shortlisting process will only start once the application due date has been reached. The time taken to complete this process will depend on how far you progress and the availability of managers. 

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