Quantitative Analyst

REQUISISTION DETAILS

REQ: 148018 Thembi Mtshali

Investment Banking

Quantitative

Manage Self: Professional

FAIS Affected

Job Purpose

Support the development and application of advanced quantitative analytics to improve credit portfolio performance, pricing decisions and risk-adjusted returns as well as Model development. Leverage data science, machine learning and automation to deliver actionable insights and innovative solutions aligned with Nedbank’s digital transformation strategy.

Job Responsibilities

• Maintain advanced analytics frameworks for credit portfolio management. • Contribute to enhancing traditional modelling approaches and apply machine learning methodologies to deliver predictive and prescriptive insights across the credit lifecycle. • Research, evaluate and assess innovative analytical techniques and methodologies to enhance model development, performance and efficiency. • Contribute to the development of origination modelling strategies and methodology to align with portfolio objectives and risk appetite. • Assist in deep dive analysis into credit portfolios to identify performance drivers, emerging risks and opportunities for strategic portfolio rebalancing. • Build interactive dashboards and visualisation tools for real-time portfolio monitoring. • Conduct pricing analytics to assess the effectiveness of risk-based pricing strategies, assess optimisation opportunities and risk-adjusted returns. • Compare model-predicted outcomes against actual portfolio performance to evaluate pricing models, assumptions and realised profitability. • Contribute to the development and enhancement of client-level pricing frameworks to support holistic relationship-based pricing, balancing customer value, risk and profitability across the client portfolio. • Support cross-sell and customer behaviour analytics that will inform and identify growth opportunities and optimise customer value. • Collaborate with stakeholders to integrate analytics into strategic planning and risk appetite frameworks. • Contribute to a collaborative and high-performance team environment through sharing knowledge, best practices and insights supporting innovation, continuous learning and professional development.

Essential Qualifications

• Degree in Mathematics, Statistics, Financial Engineering, Economics, Actuarial Science, or related quantitative field. • Postgraduate qualification or certifications in Data Science, Machine Learning or FRM/CFA advantageous.

Minimum Experience Level

• 2+ years in credit risk analytics, portfolio management or related fields. • Proven experience with SAS, Python, R and SQL analytics platforms. • Familiarity with IFRS9, Basel frameworks and advanced credit modelling techniques.

Technical / Professional Knowledge

• Strong analytical and problem-solving skills. • Strong communication and stakeholder engagement. • Curiosity and a continuous learning mindset.

Behavioural Competencies

• Adaptability

• Applied Learning

• Communication

• Continuous Learning

• Continuous Improvement

• Driving for Results

• Influencing

• Business Acumen

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