Credit Risk Data Scientist — SME Lending & Models

Hala; Riyadh; On-site; SAR 300,000 - 520,000; Full time

Job summary

HALA Financing is seeking an Actuarial Data Scientist to advance our credit engine, risk models, and portfolio monitoring. You will predict probability of default, enhance credit decisioning, and build data-driven models to support responsible SME growth.

The ideal candidate blends actuarial thinking with credit risk modelling, ML, and strong business judgment, collaborating with Credit, Risk, Product, and Data Engineering to turn insights into actionable strategies balancing growth with

Qualifications

• Bachelor’s degree in a quantitative field; Master’s preferred.
• 3–6 years in actuarial analytics, credit risk, or fintech.
• Strong understanding of PD, credit scoring, portfolio risk, delinquency, loss forecasting, and cohort analysis.
• Strong Python and SQL skills.
• Experience with statistical modelling and ML methods.
• Ability to translate analyses into business recommendations.
• Strong communication and stakeholder management.

Responsibilities

• Build, validate, and improve PD and credit scoring models.
• Analyze delinquency trends, vintage curves, and loss patterns.
• Develop early-warning indicators for delays and defaults.
• Monitor portfolio performance and report risk metrics.
• Support management and investor risk reporting.
• Collaborate with Data Engineering to improve data quality.

Skills

Python

SQL

Credit risk modelling

Statistical modelling

Machine learning

Communication skills

Stakeholder management

Education

Bachelor's degree in Actuarial Science, Statistics, Mathematics, Data Science, Computer Science, Engineering, Finance, or related field

Master’s degree preferred

Job description

HALA Financing is seeking an Actuarial Data Scientist to advance our credit engine, risk models, and portfolio monitoring. You will predict probability of default, enhance credit decisioning, and build data-driven models to support responsible SME growth.

The ideal candidate blends actuarial thinking with credit risk modelling, ML, and strong business judgment, collaborating with Credit, Risk, Product, and Data Engineering to turn insights into actionable strategies balancing growth with