Quant jobs / United Overseas Bank

Vice President, Data Scientist, Group Retail

Develop financial-crime analytical models within UOB’s retail data-science function. The role covers feature development, model recalibration and evaluation of rule-based and ML methods.

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 models for financial-crime risk detection.
Retrain and recalibrate models when performance drifts.
Test bias, document model behaviour and incorporate regulatory changes.

What they ask for

Required

Advanced analytical models
Data wrangling and machine learning
SQL, Python, R or SAS
Model governance
Technical communication

Preferred

Financial-crime analytics
NLP and network analysis

Education: Bachelor’s in computing, engineering, statistics, mathematics, business analytics or equivalent.
Experience: 6–8 years in technology, with 2–4 years using advanced analytics; at least 4 years in project management is specified.
Languages and tools: SQL
Python
R
SAS
pandas
Keras
TensorFlow
scikit-learn

How to prepare

Build an imbalanced risk-detection model with calibrated evaluation.
Test drift and subgroup performance on time-separated data.
Document features, validation and monitoring for model review.

What to study

The Model Validation Quant roadmap sets out the stages for this kind of role, with free resources for each.

Open the roadmap

Apply

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

View the posting on United Overseas Bank’s site ↗

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