Quantitative Analyst - Ops Risk and Non-Financial Risk Analytics

JREQUISITION DETAILS

REQ 146249 Thembi Mtshali

Location: Johannesburg

Closing date:  12 June 2026

Job Family

Career Stream

Leadership Pipeline

Job Purpose

This role is responsible for developing and applying advanced analytical and quantitative techniques to strengthen Operational Risk and broader Non-Financial Risk (NFR) analytics, including Conduct Risk. It focuses on enabling the organisation to better understand and quantify risk exposures, identify key risk drivers, and support forward-looking risk assessments.

Rooted in analytical thinking, statistical expertise, and first-principles problem-solving, the position supports a shift from traditional, retrospective reporting to predictive, insight-led risk management.

Operating within a second-line risk function, the role provides independent analytical capability to enhance risk measurement, generate meaningful insights, and support informed decision-making.

Job Responsibilities

Operational Risk and NFR Analytics

• Develop and apply robust analytical approaches to support the understanding and quantification of Operational Risk, Conduct Risk and behavioural risk patterns, as well as broader Non-Financial Risk dimensions such as process risk, concentration risk, and interdependencies.


• Apply quantitative techniques to analyse historical risk data, identify key relationships and underlying drivers of risk events, and contribute to the establishment of structured risk measurement methodologies.


• Supports the development of trend analysis and risk profiling, and analytical frameworks that enhance risk assessment practices.


• Perform scenario analysis, stress testing, and trend analysis to proactively anticipate and assess potential risk exposures.

Risk Insight Generation and Analytical Problem Solving

• Focus on translating complex data into clear, meaningful insights by identifying patterns, anomalies, and emerging trends, and interpreting analytical outputs within a risk management context.


• Provide a deeper understanding of why risk levels are changing, highlighting emerging areas of concern and supporting data-driven decision-making.


• Produce structured, insight-driven outputs that enhance the quality, relevance and impact of risk reporting, enabling more informed and proactive management of risk.

Risk Data Analysis and Preparation

• Work with risk-related datasets to extract, clean, and structure data in a manner that supports robust and reliable analysis, ensuring logical consistency and usability for analytical purposes.


• Develop a strong understanding of data limitations, quality issues and potential biases, as well as the underlying assumptions that may influence analytical outcomes.


• Support the creation of reusable analytical datasets and the establishment of consistent data views aligned to key risk analytics use cases, enabling more efficient and effective analysis across the risk function.

Monitoring, Trend Analysis and Forward-Looking Analytics

• Develop data-driven risk monitoring approaches and robust trend analysis across key risk indicators.


• Contribute to building forward-looking perspectives on risk exposure, enabling the early identification of emerging risks.


• Assist in developing analytical tools that enhance proactive risk monitoring capabilities and produces simplified, focused insight outputs that support effective and timely decision-making.

Stakeholder Engagement & Analytical Translation

• Involve engaging closely with stakeholders to understand key business and risk-related questions and translating these into clearly defined analytical problems.


• Present findings in a clear, strucutured and insight-focused manner that is accessible and relevant to a range of audiences.


• Support the organisation's transition toward more focused, insigt-driven communication of risk, enhancing the overall impact and effectiveness of risk reporting and decision-making.

Job Responsibilities Continue

Scenario Analysis & Risk Quantification Support

• Support the analytical components of scenario analysis by leveraging historical risk data to inform the assessment of potential future outcomes. This includes analysing past risk events to support the estimation of potential severity and impact and identifying patterns and relationships across different risk scenarios.


• Contribute to the development of structured approaches to risk quantification, ensuring that scenario assessments are grounded in data-driven insights and robust analytical methodologies.

Process, Concentration and Risk Driver Analysis

• Support analytical activities focused on assessing process risk, operational vulnerabilities, and concentration risk across key activities, services, and dependencies. This includes identifying systemic risk drivers that may influence or amplify risk exposure across the organisation.


• Assist in developing analytical views of risk concentrations and contributes to establishing structured approaches for identifying and prioritising areas of elevated risk exposure, enabling more targeted and effective risk management.

Analytical Frameworks and Model Development

• Contribute to the development of statistical and analytical models and structured approaches to analysing risk across the organisation.


• Support the testing, validation, and interpretation of analytical outputs, ensuring that insights generated are both robust and meaningful.


• Responsible for the continuous refinement of analytical methodologies, with a strong emphasis on understanding underlying principles and drivers rather than applying techniques in a purely mechanical manner.

Governance, Documentation and Risk Alignment

• Ensure that all analytical work is thoroughly documented, including methodologies, assumptions, and data logic, to maintain transparency and reproducibility.


• Emphasise alignment with internal risk frameworks, policies, and standards, ensuring that analytical outputs are consistent with organisational requirements.


• Support audit and validation processes and contributes to the continuous improvement of analytical documentation, strengthening overall governance and credibility of risk analytics.

Innovation and Continuous Improvement

• Contribute to the continuous enhancement of analytical capability by supporting the adoption of improved and more advanced analytical approaches.


• Develop knowledge of emerging techniques in data analysis and risk analytics to ensure practices remain current and effective.


• Support initiatives aimed at improving efficiency and reducing manual effort in analysis and reporting, enabling more streamlined, scalable, and value-adding risk analytics processes.

Essential Qualifications - NQF Level

Preferred Qualification

Postgraduate degree or certifications in:

• Risk Management (e.g., FRM)


• Data Science / Machine Learning


• Compliance or Operational Risk Analytics

Minimum Experience Level

• 0 (Graduate) – 3 years’ experience (including academic projects) in:

• Data analysis


• Quantitative problem solving


• Statistical or analytical work

• Prior exposure to risk environments is advantageous but not required.

Technical / Professional Knowledge

Behavioural Competencies