Purpose Statement

• The Quantitative Analyst role uses statistical, mathematical, and financial models to unpack risk based assessments and scenario analyses that supports strategic planning and optimises business performance.
• With this translation of advanced analysis to easily understandable insights, the role enables confident, evidence-based decisions and is key to the organisation’s ambition to be an insights driven enterprise.     
   

Experience

• NB. Length of experience required is conditional on the qualifications obtained  
• Experience in statistical and / or mathematical model development and deployment incl. Markov chains, runoff triangles, regression, time series, machine learning (neural networks, SVM, random forests etc.), and quantitative analysis (time value of money etc.). 
• General business know-how: e.g. risk, compliance, operations e.g. NCR, POPIA, SARB, IFRS, Basel 
• Business analysis and requirements gathering 
  Working in cloud environments e.g. Azure, AWS and large relational databases  
• Experience in SQL, R, Python, SAS or similar 
• Expert functional business area (e.g. Credit / Risk) environment knowledge and experience

Qualifications (Minimum)

Qualifications (Ideal or Preferred)

Knowledge

• Deep functional business area (e.g. Credit / Risk) knowledge and experience 
• Deep understanding of a wide range of statistical and / or mathematical models, including development and deployment principles. This includes, but is not limited to Markov chains, runoff triangles, regression, time series, machine learning (neural networks, SVM, random forests etc.), and quantitative analysis (time value of money etc.). 
• Best practices for model development and usage such as reusability, reproducibility, continuous monitoring, etc• Financial sector experience 
• Working with multiple teams to deliver quantitative models into a production environment 
• Stakeholder management at Executive and senior management level  
• Capitec Model Governance Process

Skills

Conditions of Employment