Senior Quantitative Analyst: Scorecard

Nedbank; Johannesburg; On-site; ZAR 900,000 - 1,200,000; Full time

Job summary

Nedbank invites applications for a Senior Quantitative Analyst: Scorecard to develop, calibrate and monitor client-centric acquisition scorecards and predictive credit models across Private Clients, Private Wealth and Small business lending portfolios.

You will use Python, SAS and SQL to build robust scorecards, validate models and implement production-ready decisioning strategies while driving model governance and performance monitoring.

Qualifications

• Advanced Diploma/National 1st Degree required.
• Postgraduate degree in statistics, mathematics, finance, economics, data science, engineering or related quantitative field; CFA, FRM or CQF advantageous.
• 3–5 years’ experience in scorecard and credit risk models development; proven experience with application and behavioural scoring models.

Responsibilities

• Develop, calibrate, validate, monitor and optimise client centric acquisition scorecards and predictive credit models across lending portfolios.
• Develop statistically robust scorecards using internal, bureau, and alternative data sources.
• Evaluate modelling methodologies to improve model performance and predictive power.
• Develop champion-challenger frameworks for testing traditional scorecards against machine learning models.
• Identify opportunities to leverage AI and alternative data sources to improve predictive performance and customer experience.

Skills

Analytical thinking

Communication

Stakeholder management

Education

Postgraduate degree in statistics, mathematics, finance, economics, data science, engineering or related quantitative field

Advanced Diploma/National 1st Degree

Tools

Python

SAS

SQL

Job description

Title:Senior Quantitative Analyst: Scorecard

Talent Acqusition Specialist: Noli Madikane

Job Family

Investment Banking

Quantitative

Manage Self: Professional

Job Purpose

To develop, calibrate, validate, monitor and optimise client centric acquisition scorecards and predictive credit models that support lending and credit risk strategic objectives across Private Clients, Private Wealth and Small business (PWS) lending portfolios. Add your second sentence

Job Responsibilities

• Develop, implement and enhance client centric acquisition scorecards and predictive credit models across PWS lending portfolio using Python/SAS and SQL.
• Develop statistically robust scorecards using internal, bureau, and alternative data sources.
• Evaluate emerging modelling methodologies and techniques to improve model performance and predictive power.
• Develop champion-challenger frameworks for testing traditional scorecards against Machine learning models.
• Identify opportunities to leverage AI and alternative data sources to improve predictive performance, customer experience, and financial inclusion.
• Drive innovation initiatives focused on improving risk prediction, customer acceptance rates, pricing optimisation and portfolio profitability.
• Extract, analyse and interpret large datasets using SAS, SQL and other analytical tools to identify trends and opportunities.
• Monitor scorecard and model performance and recommend recalibration, redevelopment or optimisation where required.
• Conduct model validation, performance assessments and ongoing model health monitoring.
• Support the implementation, testing and deployment of scorecards and decisioning strategies within production environments.
• Produce regular portfolio performance analysis and provide actionable recommendations to business stakeholders.
• Partner with Risk, Business, Finance, Operations and Technology teams to support strategic decision-making.
• Contribute to the development and optimisation of credit risk strategies through advanced analytics and quantitative techniques.
• Ensure compliance with internal model governance standards, regulatory requirements and policy frameworks.
• Develop and maintain model documentation, governance packs and stakeholder reporting.
• Improve efficiencies through automation, optimisation and continuous improvement of analytical processes.
• Perform impact assessments and analyses to support new products, initiatives and strategic projects.
• Identify opportunities to improve data quality, reporting capabilities and analytical methodologies.
• Communicate analytical findings and recommendations clearly to technical and non-technical stakeholders.
• Stay abreast of industry trends, analytical methodologies and emerging technologies relevant to credit risk and scorecard development.

Essential Qualifications - NQF Level

• Advanced Diplomas/National 1st Degrees

Preferred Qualification

• Postgraduate Degree in Statistics, Mathematics, Finance, Economics, Data Science, Engineering or a related quantitative field, and CFA, FRM or CQF,

Minimum Experience Level

• 3-5 years’ experience in scorecard and credit risk models development
• Proven experience developing and implementing application and behavioural scoring models.
• Experience in bureau score utilisation, reject inference, calibration, validation, and model monitoring.
• Advanced Python, SAS and SQL programming experience is essential.
• Experience with model implementation, testing and performance monitoring.
• Paragon Modeller is an advantage

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
• Coaching
• Communication
• Decision Making
• Quality Orientation
• Technical/Professional Knowledge and Skills

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Nedbank Ltd Reg No 1951/000009/06.
Authorised financial services and registered credit provider (NCRCP16).