Senior Data Scientist, Credit Risk & Lending (Banking)

Salt; Abu Dhabi; On-site; AED 30,000 - 32,000; Full time

Job summary

Salt is seeking a hands-on Senior Data Scientist with banking or financial services experience, particularly in credit risk and lending. You will develop machine learning solutions for loan underwriting, default prediction, and customer analytics, with ownership across model development, validation, deployment and monitoring.

The ideal candidate should have strong technical fundamentals and be able to explain modelling decisions and business outcomes clearly.

Qualifications

• Proven ML project delivery with ownership of decisions and outcomes.
• Banking/financial services experience with credit risk or lending modelling.
• Strong Python/SQL skills for data prep, analysis and modelling.

Responsibilities

• Translate business needs into modelling objectives with measurable success criteria.
• Develop models for credit scoring, underwriting, and default prediction.
• Analyze credit bureau, transactional and behavior data to improve risk assessment.
• Perform data prep, feature engineering, and feature selection.
• Build and compare models using Random Forest, XGBoost, LightGBM, CatBoost.
• Conduct hyperparameter tuning and validation such as cross-validation and time-based tests.
• Evaluate models and select thresholds aligned with business priorities.
• Explain model behavior and individual predictions using SHAP.
• Collaborate with engineering to deploy models and monitor performance.

Skills

Python

SQL

Credit risk modelling

Machine learning

Model deployment

Data analysis

Tools

AWS SageMaker

XGBoost

LightGBM

CatBoost

SHAP

Job description

Salt is seeking a hands-on Senior Data Scientist with banking or financial services experience, particularly in credit risk and lending. You will develop machine learning solutions for loan underwriting, default prediction, and customer analytics, with ownership across model development, validation, deployment and monitoring.

The ideal candidate should have strong technical fundamentals and be able to explain modelling decisions and business outcomes clearly.