Lead Quantitative Analyst â Advanced Analytics

Recruiter:

Network Recruitment

Job Ref:

NFP016799/ZG

Date posted:

Thursday, May 7, 2026

Location:

Stellenbosch, South Africa

Salary:

Annually

SUMMARY:
A leading South African retail bank is expanding its advanced analytics and machine learning capabilities and is seeking a Lead Quantitative Analyst – Advanced Analytics to independently validate highâimpact models across credit risk, financial crime, and broader advanced analytics use cases.

POSITION INFO:
This is a handsâon technical role for an experienced machine learning professional who enjoys working endâtoâend on complex models in a regulated environment and providing strong analytical challenge to production models.

You will play a key role within a specialist quantitative function responsible for the independent validation and oversight of machine learning and data science models used across the organisation. These models support critical decisionâmaking in areas such as credit risk, fraud, AML, and customer behaviour.

The role combines deep technical modelling work with leadership responsibilities, including mentoring junior analysts and partnering closely with Risk, Technology, and Business teams to ensure that models are robust, scalable, and productionâready.

Key Responsibilities:

Lead independent validation of machine learning models, including:
- Credit risk models
- Propensity and behavioural models
- Financial crime models (fraud and AML)
Apply advanced machine learning techniques such as:
- Supervised learning (Random Forest, XGBoost, CatBoost, and Neural Networks)
- Unsupervised learning (clustering, isolation forests, and anomaly detection)
Manage model risk across the full model lifecycle, including:
- Feature engineering and data preparation
- Model training, evaluation, and selection
- Deployment readiness and ongoing monitoring
Build, assess, and review models in Python based environments
Provide technical leadership and mentorship to analysts and junior data scientists
Partner with Risk, Technology, and Business stakeholders on model oversight
Ensure adherence to governance, performance, and scalability standards

Job Experience and Skills Required:

Education:
- Honours or Master’s degree in Mathematics, Statistics, Computer Science, Actuarial Science, or a related quantitative field
Experience:
- 6–8+ years’ experience in data science, machine learning, or quantitative analytics
- Hands on leadership experience delivering models end-to-end
- Experience in credit risk, propensity modelling, and/or financial crime
- Exposure to independent model validation or strong peer review
- Experience in regulated environments
Skills:
- Machine learning techniques: XGBoost, CatBoost, Random Forest, and Neural Networks
- Clustering and anomaly detection
- Advanced Python and solid SQL skills
- Strong understanding of the full model lifecycle
- Ability to work across technical and business stakeholders

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