Quantitative Analyst

Afrizan Personnel; Sandton; Hybrid; ZAR 500 000 - 800 000; Full time

Job summary

A leading financial services firm is seeking a skilled Quantitative Analyst to join their Group Risk Analytics team in Sandton. This role involves developing advanced credit portfolio analytics frameworks and leveraging machine learning to optimize credit strategy. Candidates should hold a degree in a quantitative field and have strong skills in SAS, Python, R, and SQL. The position promotes innovation and analytics in decision-making, offering a modern, hybrid working environment.

Qualifications

• Minimum of two years' experience in credit risk analytics or quantitative modelling.
• Proficiency in SAS, Python, R, and SQL.
• Working knowledge of IFRS 9, Basel frameworks, and advanced credit modelling techniques.

Responsibilities

• Develop and maintain advanced credit portfolio analytics frameworks.
• Apply machine learning and advanced statistical techniques to improve predictive accuracy.
• Perform in-depth portfolio analysis including RWA and Economic Capital attribution.

Skills

Quantitative analysis

Machine learning

Statistical techniques

SAS

Python

R

SQL

Analytical ability

Problem-solving skills

Education

Degree in Mathematics, Statistics, Financial Engineering, Economics, or Actuarial Science

Postgraduate qualification or certifications in Data Science, Machine Learning, FRM or CFA

Job description

Quantitative Analyst Afrizan Personnel•Sandton

Job Description

Are you a quantitative thinker who thrives on turning complex credit data into powerful, commercial insight?

A leading financial services client is seeking a Quantitative Analyst – Credit Portfolio Analytics to join a high-impact Group Risk Analytics team. This role offers the opportunity to work at the forefront of advanced analytics and machine learning, shaping credit strategy and optimising risk-adjusted returns within a modern, hybrid working environment based in Sandton, Johannesburg.

• Develop and maintain advanced credit portfolio analytics frameworks
• Apply machine learning and advanced statistical techniques to improve predictive accuracy
• Perform in-depth portfolio analysis, including RWA and Economic Capital attribution and optimisation
• Design dashboards and visualisation tools for real-time portfolio monitoring
• Partner with stakeholders to embed analytics into risk appetite and strategic decision-making
• Contribute to innovation, knowledge sharing and continuous improvement initiatives

Key requirements

• Degree in Mathematics, Statistics, Financial Engineering, Economics, Actuarial Science or a related quantitative field
• Postgraduate qualification or certifications in Data Science, Machine Learning, FRM or CFA (advantageous)
• At least two years’ experience in credit risk analytics, quantitative modelling or a similar environment
• Strong proficiency in SAS, Python, R and SQL
• Working knowledge of IFRS 9, Basel frameworks and advanced credit modelling techniques
• Excellent analytical ability, problem-solving skills and stakeholder communication

EE Disclaimer:

All positions will be filled in accordance with the company's Employment Equity plan. We encourage people with disabilities to apply.

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