Senior Quantitative Analyst at Nedbank

Job Purpose

• Group Risk Analytics is the cornerstone of analytical excellence in Group Risk with a strong focus on a wide array of analytics ranging from Credit, Conduct, Financial and Operational Risk analytics. 
• Our passion is finding meaning in data and using analytical insights to influence decision making. As a member of Group Risk Analytics, you will collaborate with other analytics teams to find analytical solutions to high-value business problems. 

Job Responsibilities

• As a Quantitative Analyst within the Credit Risk Systems division, you will drive innovation and operational excellence by leveraging advanced analytics and modern data engineering practices. Your work will directly influence strategic decision-making and model sustainability across the IFRS 9 impairment landscape.

Role Purpose

• To maintain best practice models and assessment strategies in line with regulations (where applicable) in order to facilitate world class risk management and/or attainment of strategic objectives.

Key Responsibilities
Process Optimisation & Automation

• Identify and implement opportunities to streamline business-as-usual processes using data-driven insights, automation tools, and scalable analytics solutions.
• Drive the implementation and adoption of modern data workflows (e.g., cloud-based pipelines, version-controlled model groups, Risk Governance Frameworks and continuous modernisation of the platform) to improve efficiency and reproducibility.

Advanced Risk Analytics

• Apply statistical and other techniques to analyse drivers of credit risk and IFRS 9 impairments.
• Implement models using SAS, Python, or other relevant platforms, ensuring alignment with risk, finance and audit requirements.

Solution Engineering & Stakeholder Engagement

• Collaborate with cross-functional teams to design and deliver superior analytical solutions that meet evolving business needs.
• Translate complex analytical findings into actionable insights and communicate them effectively to technical and non-technical stakeholders.

Model Lifecycle Management

• Lead model optimisation and readiness assessments for SAS IFRS 9 implementations, ensuring robustness, scalability, and auditability.
• Explore and implement innovative techniques that enhance model sustainability and reusability.

Data Exploration & Ad Hoc Analysis

• Extract, clean, and analyse large datasets to support business queries, regulatory submissions, and strategic initiatives.
• Perform ad hoc analyses and respond to data requests with precision and speed, ensuring data integrity and relevance.

Compliance & Monitoring

• Ensure ongoing compliance with internal policies through proactive data monitoring and analysis.
• Support risk governance by identifying anomalies, trends, and potential areas of concern in macroeconomic forecasts used in the impairment process.
• Effective RDARR remediation of in scope reports, including the enforcement credit data standards and policies

Insight Generation & Strategic Support

• Deliver impactful insights through analytical research, system performance reviews, and marketing analytics.
• Provide recommendations that support business growth, risk mitigation, and strategic planning.

Documentation & Knowledge Management

• Maintain comprehensive documentation of models, processes, and analytical workflows to support continuity, transparency, and audit readiness.
• Documentation of business requirements and user acceptance testing, including prototyping
• Contribute to the team's knowledge base by sharing best practices and lessons learned.

Intentional growth

• Improve personal capability and stay abreast of developments in field of expertise by identifying training courses and career progression for self through input and feedback from managers.

Essential Qualifications - NQF Level

• Advanced Diplomas/National 1st Degrees

Essential Qualification

• Formal Qualification    Undergraduate degree in Statistics/Mathematics
• Post graduate degree in Statistics/Mathematics, CFA/ FRM/ CQF (preferred)

Minimum Experience Level

• 3-5 years relevant experience in an analytical environment

Types exof exposure

• Credit (e.g. risk, strategy, origination, pricing) knowledge
• Analytical/quantitative skills
• Communication and reporting skills (verbal and written)
• Intermediate programming skills (e.g. VBA, MATLAB, SAS, R), advanced SAS and SQL skills preferred / SAS accreditation.
• Excellent writing and presentation skills

Technical / Professional Knowledge

• Industry trends
• Microsoft Office
• Principles of project management
• Relevant regulatory knowledge
• Relevant software and systems knowledge
• Risk management process and frameworks
• Business writing skills
• Microsoft Excel
• Business Acumen
• Quantitative Skills

Behavioural Competencies

• Applied Learning
• Coaching
• Communication
• Collaborating
• Decision Making
• Continuous Improvement
• Quality Orientation
• Technical/Professional Knowledge and Skills