Quantitative Risk Analyst at The Mutual Insure | Apply Now!

Job Details

🏢 Company: Old Mutual Insure
📍 Location: Johannesburg, South Africa
💼 Job Title: Quantitative Risk Analyst
🕒 Employment Type: Full-Time
⏳ Closing Date: 13 January 2026 (23:59)
🆔 Job Requisition ID: JR-74894
📊 Business Area: Risk Management / Data Science

Company Overview

Old Mutual Insure is deeply rooted in Africa’s growth story and is committed to building innovative, data-driven insurance solutions that are predictive, fair, and scalable. By combining strong governance with advanced analytics, Old Mutual Insure continues to modernise how insurance risk is measured, monitored, and managed across the business.

Job Purpose

The Quantitative Risk Analyst will join a high-performance team modernising the second-line risk function through a code-first, automation-led approach. The role focuses on replacing manual reporting and traditional compliance frameworks with real-time monitoring, automated validation pipelines, and advanced analytics. This position is ideal for a technically strong, systems-oriented professional who thrives in solving complex, unstructured risk challenges using data, machine learning, and emerging technologies.

Key Responsibilities

• Build end-to-end automated solutions to validate, benchmark, and monitor insurance risk models

• Develop and maintain statistical and machine learning models for credit, market, operational, and emerging risks

• Design predictive models that act as early warning indicators for potential risk events

• Apply advanced techniques such as LLM-based agents to interpret regulatory changes and graph theory for fraud network detection

• Extract insights from both structured and unstructured datasets

• Ensure high standards of data quality, integrity, lineage, and regulatory compliance

• Collaborate closely with First Line teams and other stakeholders to develop best-practice risk frameworks and policies

• Challenge existing data processes and recommend improvements to enhance reliability and scalability

• Contribute to a code-first risk environment using clean, testable, version-controlled codebases

• Support continuous improvement by simplifying, automating, and scaling risk processes wherever possible

Required Qualifications

Education

• Bachelor’s degree (NQF Level 7 or equivalent) in one of the following:

  • Data Science

  • Statistics

  • Actuarial Science

  • Engineering

  • Physics

  • Mathematics or Applied Mathematics

Experience

• Minimum of 4 years’ experience in actuarial science, data science, or quantitative risk analysis

• Proven experience within financial services or insurance environments

• Hands-on experience working with large datasets and analytical models

Technical Skills & Knowledge

• Strong proficiency in Python for statistical modelling and analytics

• Experience working in version-controlled environments with code review processes

• Solid SQL skills and experience handling large-scale datasets

• Understanding of risk management frameworks and insurance risk processes

• Knowledge of CI/CD practices, unit testing, and clean code principles

Advantageous

• Progress toward actuarial qualification or a postgraduate degree in statistics or data science

• Experience using Generative AI and Large Language Models (LLMs) for unstructured data analysis

• Exposure to advanced analytics for fraud detection and regulatory interpretation

Competencies & Attributes

• Strong business insight and commercial awareness

• Ability to manage ambiguity and complex problem spaces

• Analytical mindset with disciplined execution and delivery focus

• Collaborative approach across technical and business teams

• Curiosity and willingness to experiment with new tools, AI trends, and methodologies

• Resilience when handling competing priorities and tight deadlines

CV Tips for This Role

• Highlight Python-based modelling projects and automated analytics solutions

• Showcase experience in insurance, financial services, or risk environments

• Emphasise clean code practices, CI/CD exposure, and version control workflows

• Include examples of predictive modelling, machine learning, or AI-driven analysis

Company Policy

Old Mutual South Africa is committed to transformation and employment equity. Appointments will be made in line with the Employment Equity Plan, and preference will be given to candidates from designated groups in accordance with applicable legislation. Old Mutual reserves the right not to make an appointment to the advertised position.