Western Cape: Lead Quantitative Analyst (advanced analytics) posted by Network Finance

This is a handson technical role for an experienced machine learning professional who enjoys working endtoend on complex models in a regulated environment and providing some strong analytical challenges 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 decisionmaking 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 productionready.

Key Responsibilities:

• Lead the 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

Responsibilities:
Perform monthly and quarterly actuarial valuations
Support IFRS 17 reporting and related calculations
Assist with statutory and embedded value reporting
Conduct reserving and liability calculations
Perform experience investigations and forecasting analysis
Develop, maintain, and improve actuarial models and reporting tools
Extract, analyse, and validate data using SQL
Prepare reports for regulatory and internal stakeholders
Collaborate with Finance, Risk, and Product teams on reporting requirements
Ensure compliance with actuarial governance and reporting standards
Job Experience and Skills Required:
Education:
Actuarial degree
Experience:
Minimum 4 years’ actuarial experience within life insurance
Strong valuations experience
IFRS 17 reporting exposure essential
Experience within financial reporting and reserving
Progress toward actuarial qualification advantageous
Skills:
Minimum 8 actuarial exams completed
Strong SQL experience
Excellent analytical and problem-solving ability
Strong communication and stakeholder engagement skills
Ability to work independently and within a collaborative team