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31 May
2026
Permanant Model Risk Specialist (Data Scientist) | FirstRand Vacancies
Job Description
FirstRand Vacancies – Model Risk Specialist (Data Scientist)
Job Type: Full Time
Company: FirstRand
Model Risk Specialist (Data Scientist)
We are seeking a highly analytical and detail-oriented Model Risk Specialist (Data Scientist) to join a dynamic Enterprise Risk Management team. The successful candidate will be responsible for performing independent model validation, assessing model risk, enhancing governance frameworks, and ensuring that models used across the organization are accurate, reliable, and aligned with regulatory and business requirements.
This role offers the opportunity to work with a wide range of quantitative models while contributing to risk management, governance, and strategic decision-making processes.
Key Responsibilities
Model Validation and Risk Management
- Perform independent validation of quantitative, statistical, and predictive models.
- Review and reperform model development processes to assess accuracy, robustness, and appropriateness.
- Evaluate model assumptions, methodologies, data quality, and performance.
- Assess model limitations and identify potential model risks.
- Provide independent assurance on the suitability and effectiveness of models used within the business.
- Monitor model performance and recommend enhancements where required.
Governance and Framework Development
- Contribute to the development and enhancement of model risk management frameworks.
- Review and assess modelling standards, policies, procedures, and governance practices.
- Ensure alignment between modelling activities, risk frameworks, and business objectives.
- Support continuous improvement of model governance processes and controls.
- Assist in strengthening enterprise-wide model risk management practices.
Reporting and Stakeholder Engagement
- Prepare detailed validation reports, findings, and recommendations.
- Communicate validation outcomes, model risks, and corrective actions to stakeholders.
- Present findings and recommendations to governance committees and decision-making forums.
- Build and maintain strong working relationships with model developers, risk teams, and business stakeholders.
- Provide expert guidance on model risk management and validation best practices.
Research and Methodology Enhancement
- Conduct research into emerging modelling methodologies, regulatory developments, and industry best practices.
- Evaluate new analytical techniques and modelling approaches.
- Support innovation and continuous improvement within the model risk management function.
- Contribute to the advancement of validation methodologies and analytical frameworks.
Requirements
- Bachelor’s Degree in Statistics, Mathematics, Data Science, Actuarial Science, Quantitative Risk Management, Engineering, Economics, or a related quantitative discipline.
- Honours Degree or postgraduate qualification will be advantageous.
- Minimum of 2–4 years of experience in model validation, financial modelling, quantitative analysis, risk modelling, or model risk management within the financial services sector.
- Experience working with quantitative models in banking, financial services, or risk management environments.
- Strong understanding of model development, validation methodologies, and model governance principles.
Technical Skills
- Proficiency in programming and analytical tools including:
- Python
- SAS
- SQL
- R
- Microsoft Excel
- Experience with statistical modelling, predictive analytics, and data analysis.
- Strong understanding of model performance testing and validation techniques.
- Ability to work with large and complex datasets.
Preferred Experience
Experience validating, developing, or assessing the following model types will be advantageous:
- Credit application scorecards.
- Behavioral scorecard models.
- Credit risk regulatory capital models.
- Expected credit loss and provisioning models.
- Financial crime and fraud detection models.
- Treasury and liquidity risk models.
- Artificial Intelligence and Machine Learning models.
- Risk management and regulatory compliance models.
Skills and Competencies
- Strong analytical and quantitative problem-solving abilities.
- Excellent attention to detail and investigative skills.
- Strong report writing and presentation capabilities.
- Ability to communicate complex technical concepts to both technical and non-technical audiences.
- Strong stakeholder management and relationship-building skills.
- Sound judgment and decision-making abilities.
- Ability to work independently and manage multiple priorities.
- Commitment to accuracy, quality, and continuous improvement.
- Strong understanding of governance, controls, and risk management principles.
Knowledge and Expertise
- Model risk management frameworks and governance.
- Statistical modelling and predictive analytics.
- Financial risk management principles.
- Banking and financial services regulatory environments.
- Quantitative analysis and validation methodologies.
- Data science and machine learning concepts.
- Regulatory expectations related to model governance and validation.
What We Offer
- Opportunity to work in a challenging and highly analytical risk environment.
- Exposure to a wide range of advanced quantitative and predictive models.
- Involvement in strategic risk management and governance initiatives.
- Professional growth and development opportunities.
- Collaborative environment that encourages innovation and continuous improvement.
- Opportunity to influence model risk management practices across the organization.
Conditions of Employment
- Clear criminal record.
- Ability to maintain the highest standards of integrity, professionalism, and confidentiality.
- Commitment to regulatory compliance and risk management excellence.
If you are passionate about data science, quantitative analysis, model validation, and risk management, we encourage you to apply for this exciting Model Risk Specialist (Data Scientist) opportunity and help strengthen the integrity and effectiveness of critical business models.
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