Credit Risk Modelling Data Scientist
Hala
Job details
HALA, a leading fintech company in the MENAP region, is seeking a Credit Risk Modelling Data Scientist for its Data & Business Intelligence team in Riyadh, Saudi Arabia. This full-time role at Hala Financing focuses on developing credit engines, risk models, and portfolio monitoring capabilities to predict default probability, improve credit decisioning, and enhance risk segmentation for SME lending. Candidates should possess a Bachelor’s degree in a quantitative field (Master’s preferred) and 3-6 years of experience in actuarial analytics, credit risk, or financial modelling, along with strong Python, SQL, and machine learning skills. Key responsibilities include building risk models, monitoring portfolio performance, applying data science techniques, and collaborating with various business teams. HALA offers a competitive compensation package, personal development opportunities, and a diverse, inclusive work environment.
Advertised position
Credit Risk Modelling Data Scientist
Job overview
Source
Hala
Qualification
Bachelor’s degree in Actuarial Science, Statistics, Mathematics, Data Science, Computer Science, Engineering, Finance, or a related quantitative field; Master’s degree preferred.
Type
Full-time
Location
Riyadh
Listed
20d ago
How to apply
- 1Complete the online application form.
- 2Provide personal details including First Name, Last Name, Email, Phone, and Country.
- 3Attach your Resume/CV or enter details manually.
- 4Optionally attach a Cover Letter, LinkedIn Profile, and Website.
- 5Answer all required screening questions regarding salary, nationality, residency, experience, leadership positions, and knowledge about Hala.
Rules & eligibility
- Strong understanding of probability of default, credit scoring, portfolio risk, delinquency, loss forecasting, and cohort/vintage analysis.
- Strong skills in Python and SQL.
- Experience with statistical modelling, machine learning, regression, classification models, decision trees, gradient boosting, model validation, and performance monitoring.
- Ability to translate complex analytical findings into simple business recommendations.
- Strong communication skills and ability to work with both technical and non-technical stakeholders.
Details extracted automatically from the official advertisement — always verify against the original ad before applying.
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