Intern, Credit Risk Modelling – AI and Analytics (Jan–May 2027)

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.

• Help build a feature store for the credit model lifecycle
• Prototype AI-assisted monitoring and insight tools for model performance
• Use AI tools to speed up model documentation and governance checks
• Analyse datasets to spot trends that could improve risk processes
• Research AI use cases that suit credit risk modelling

What they ask for

Required

• Interest in AI, GenAI and data analytics
• Comfort with data and quantitative analysis
• Problem solving and critical thinking
• Awareness of responsible AI, privacy and security
• Written and verbal communication
• Currently studying for a degree

Preferred

• Programming or data analytics experience

Education

Currently studying for an undergraduate or postgraduate degree

Experience

Students; no prior experience stated

Markets

credit

How to prepare

• Build a basic credit scoring pipeline and understand each lifecycle stage from data to monitoring
• Learn what a feature store is and prototype a tiny one with pandas
• Try using an LLM to summarise model documentation, then check its errors systematically
• Read about responsible AI and model risk guidance for banks
• Practise explaining a technical model result to a non-technical reader in one page

What to study

• Python and Data Primer
• Probability, Statistics and Financial Data
• Financial Machine Learning
• Quantitative Risk Management
• Text as Data and NLP for Finance

Apply

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

View the posting on OCBC’s site ↗

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

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