Job Details

Credit Quantitative Analyst

About

Description

A credit risk analytics role focused on the development, optimisation, and ongoing monitoring of credit origination and underwriting strategies. The analyst applies advanced quantitative analysis and credit risk expertise to support responsible growth, profitability, and portfolio quality across lending products, working closely with Product, Data, Operations, and Finance teams.

Responsibilities

Credit Originations & Underwriting Strategy
Develop, analyze, and continuously improve credit origination strategies.
Optimize scorecard cut-offs, banding strategies, and decision thresholds.
Assist in designing, implementing, and maintaining credit policy rules.
Support loan pricing and credit limit strategies with risk-based pricing principles.
Perform portfolio segmentation analysis.
Credit Risk & Analytics
Develop, enhance, and monitor decisioning frameworks for underwriting.
Monitor key origination and early-life performance metrics (approval rates, bad rates, roll rates, vintage performance).
Conduct scenario analysis and stress testing on strategy changes.
Data Preparation & Feature Engineering
Clean and preprocess raw credit data.
Create relevant features for credit risk modelling.
Source, consolidate, and analyse large datasets; identify anomalies/trends.
Risk Governance & Stakeholder Collaboration
Work cross-functionally to embed originations strategies into systems and workflows.
Support governance forums with insights, recommendations, and performance reporting.
Contribute to refining risk appetite, lending standards, and credit risk frameworks.

Qualifications

Education: Bachelor's degree in Statistics, Mathematics, or related fields.
Experience:
2 – 4 years' experience in Financial Services.
Minimum 2 years' experience in a retail credit risk analysis role, understanding the entire retail credit risk lifecycle (originations, collections, regulatory capital, and IFRS 9).
Technical Skills:
Proficiency in programming languages (e.g., SAS, Python) – machine learning experience is advantageous.
Strong skills in analytics software, BI analysis, data modeling, and statistical analysis.
Key Competencies: Business insight, cultivates innovation, manages complexity, optimizes work processes, situational adaptability, and strategic mindset.