Credit Risk Model Manager

What you’d work on

Our reading of the posting: what a new hire in this role would most likely spend their first months on.

• Develop and refine PD, LGD, EAD, scorecard and IFRS 9 models
• Apply statistical and machine learning methods to lift predictive power
• Monitor stability, discrimination and calibration, and recommend recalibration
• Coordinate validation and fix findings
• Support regulators and audits with documentation

What they ask for

Required

• Bachelor's or higher in a quantitative field
• 5-8 years in credit risk modelling, analytics or validation
• Developing or managing PD, LGD, EAD, IFRS 9 or scorecard models
• Model risk governance
• SAS, Python, R or SQL
• Basel and IFRS 9 understanding

Preferred

• Master's degree
• Machine learning and predictive modelling

Education

Bachelor's or higher in statistics, maths, economics, finance, engineering or computer science; master's preferred

Experience

5-8 years in credit risk modelling, analytics, validation or risk management

Languages and tools

• SAS
• Python
• R
• SQL

Markets

credit

How to prepare

• Build a behavioural scorecard on public credit data with WoE binning and logistic regression
• Compute Gini, KS and calibration plots and set monitoring thresholds
• Study IFRS 9 expected credit loss, including lifetime PD and LGD estimation
• Compare scorecards with gradient boosting and learn the explainability trade-offs

What to study

• Quantitative Risk Management
• Probability, Statistics and Financial Data
• Financial Machine Learning
• Python for Quantitative Finance
• Econometrics and Financial Time Series

Apply

Read the full posting on UOB’s site before applying: requirements, location and pay can change after we check them.

View the posting on UOB’s site ↗

SelfMadeQuant wrote this summary from the employer’s public posting, last checked 6 November 2026. SelfMadeQuant isn’t affiliated with UOB and doesn’t handle applications.

Similar roles