About the role:

We are on a mission to bring subprime lending to the Fintech 2.0 horizon! Our way forward is to provide sustainable, scalable and embedded financial solutions to a wider range of customers that are often excluded by the traditional banks! We are looking for a passionate Data Scientist to join our Risk Function and take ownership of the full lifecycle of our consumer credit risk models. You will develop, calibrate and maintain scorecards and IFRS 9 models, monitor performance, and ensure full documentation and regulatory compliance. This is a high-impact role where you will help shape the entire risk modelling framework of a highly ambitious financial institution.

Key Responsibilities:

Risk Modelling & Analytics

• Develop, calibrate, and maintain consumer credit risk models, including:

• Application scorecards
• Behavioral scorecards
• Risk segmentation and affordability models

• Build and maintain PD, LGD, and EAD models for IFRS 9 Expected Credit Loss (ECL) calculations.
• Use advanced ML methods (e.g., CatBoost, gradient boosting) where suitable for challenger models.

IFRS 9 Modelling

• Maintain and enhance the IFRS 9 ECL model, including staging logic, macroeconomic overlays, and model calibration.
• Support the monthly and quarterly provisioning cycles with high-quality analytics.

Model Monitoring & Validation

• Perform regular model monitoring: Gini/ROC, KS, calibration, PSI/CSI, back-testing.
• Conduct annual validation and coordinate external validator/auditor reviews.
• Identify model weaknesses and propose improvements or recalibrations.

Documentation & Governance

• Maintain complete model documentation (methodology, data, assumptions, validation results).
• Ensure compliance with internal Risk Policies, IFRS 9 guidance, and audit requirements.
• Prepare model performance updates for the Risk Committee.

Data & Systems

• Work with Data Engineering to improve data pipelines and ensure data quality.
• Build reproducible analytical workflows in Python/R, SQL.
• Support deployment of models into production systems and decision engines.

Requirements:

Technical Skills

• 2+ years of experience in credit risk modelling, data science, or advanced analytics.
• Strong programming skills in Python (mandatory) plus solid SQL.
• Experience and good understanding of tree-based models, boosting, sampling techniques, deep learning
• Hands-on experience building:

• Logistic regression scorecards with WOE/IV
• PD/LGD/EAD models
• IFRS 9 provisioning models is a plus

• Strong understanding of model monitoring metrics: Gini, ROC, KS, PSI, calibration curves.

Education

• Bachelor’s or Master’s degree in Statistics, Mathematics, Data Science, Econometrics, Finance, Physics or similar.

Soft Skills

• Excellent analytical and problem-solving skills.
• Strong attention to detail and documentation discipline.
• Ability to work cross-functionally (Risk, Finance, IT, Product).
• Good communication skills in English.

We offer

• A future in a dynamic company passionate about innovation and fintech services
• Potential growth based on performance
• Opportunity to experiment with and apply innovative scoring methodologies
• Very friendly, supportive and non-conflict working environment

Please be informed that only short-listed candidates will be contacted. All applications will be treated in strict confidentiality