Quantitative Analyst

Support the development, refinement, testing, deployment, and maintenance of quantitative models, dashboards, and analytics solutions in accordance with group methodologies and/or industry best practices. Build foundational expertise in data science, risk modelling, and commercial acumen to enable independent delivery of high-impact solutions across the Nedbank value chain. They support senior quantitative analytics teams by collecting, cleaning, and analysing data that forms the foundation for complex quantitative solutions.

Domain and Technical Expertise

• Acquire and continuously develop/improve deep expertise in banking products, services and risk management.
• Acquire and continuously develop/improve deep domain expertise in quantitative analytics and their application across various risk types and specialised functional.
• Conduct research and analysis to build, maintain and continuously refine mathematical and statistical models and quantitative solutions.

Collaboration and Development

• Leverage mentorship and guidance from Senior Quantitative analysts and the broader quantitative teams regarding best practices and research to calibrate and validate model and quantitative solution components.
• Collaborate with senior quantitative analysts to commercialise quantitative models and embed them into production systems.

Model Design and Development

• Contribute to the build and maintenance of domain specific models and quant solutions (e.g. credit, pricing, market risk, trading, liquidity, impairments).
• Apply statistical and machine learning techniques to extract insights and improve model performance.
• Ensure accuracy and stability of quantitative solutions and models (and or contributions) while considering the business impact.
• Contribute to testing of components of complex quantitative solutions using multiple testing methods (e.g. back testing, stress testing, unit testing, integration testing, system testing, regression, black box, sanity, conformance, acceptance, forward etc.).
• Analyse quantitative solutions or statistical models (e.g. machine learning, NLP, etc.) outputs using various techniques and methodologies.
• Engineer and validate large datasets for model consumption, ensuring quality and integrity.

Documentation, Governance and Insight Generation

• Translate quantitative solutions and model outcomes into actionable business insight and prepare communications (reports, presentations, etc.) tailored to different audiences to enable support and decision making.
• Work within and across quantitative teams to document models, assumptions, methodologies, and other artefacts ensuring validity, reliability and explainability in the commercial and regulatory context within which the organisation operates.
• Produce high-quality model documentation of methodologies, assumptions, and data lineage to support reperformance, audit trail as well as regulatory and internal governance requirements.

Delivery management

• Work and collaborate within and across teams, senior analysts and digital/technology teams to develop, maintain, enhance and deploy scalable models.
• Support senior analysts and broader quantitative teams in the business change management and capability development processes related to the deployment of model/quantitative solutions.
• Ensure agile delivery, cross functional collaboration and deployment readiness of models.

People

• Participate in multi-disciplinary/cross functional/business teams to design and deploy quant solutions.
• Provide and receive peer reviews and constructive feedback.
• Adopt a development mindset, demonstrating commitment, learning agility and an independent drive for continuous improvement and growth towards independent design and delivery of quantitative solutions.
• Participate as a member of agile teams (sometimes multiple simultaneously) and deliver within continuously evolving strategic contexts and domain areas.
• Actively contribute to a culture of innovation and continuous learning within the greater quant community.

Governance, Risk and Finance

• Comply with both internal risk governance frameworks and external regulations, ensuring both integrity of quantitative solutions developed and adherence to conduct requirements (e.g., independence between model development and validation, SAS MRM Standards.)
• Develop an understanding of the regulatory requirements and various standards (e.g. IFRS, Basel, etc.), ensuring their effective implementation in all relevant quantitative solutions…