Senior Data Scientist

About the Opportunity:

We're partnering with an innovative early-stage fintech. As the business continues to scale, they're looking for a Senior Data Scientist to lead the development of credit risk models that will power real-world lending decisions. This is a hands-on, individual contributor role with significant ownership and the opportunity to shape the company's risk modelling capability from the ground up.

What You'll Be Doing

• Develop and own end-to-end credit risk models, including Probability of Default (PD), Loss Given Default (LGD), Exposure at Default (EAD), and Expected Credit Loss (ECL).
• Design, train, validate, and deploy production-grade machine learning and statistical models.
• Build robust credit scorecards using techniques such as WOE/IV, calibration, monotonic binning, and reason codes.
• Engineer high-quality features from lending, transactional, bureau, and financial data.
• Monitor model performance, stability, and drift while continuously improving predictive accuracy.
• Work closely with engineering and product teams to integrate models into production systems.
• Produce model documentation and validation artefacts suitable for internal governance and regulatory review.

What We're Looking For

• 6+ years of experience building & deploying credit risk models within a fintech, digital bank, or regulated lender.
• Strong understanding of PD, LGD, EAD, IFRS 9, Basel, and Expected Credit Loss (ECL) methodologies.
• Proven experience developing credit scorecards and model validation techniques.
• Strong Python skills with experience using libraries such as pandas, scikit-learn, XGBoost, LightGBM, or CatBoost.
• Experience working with large, complex financial datasets and applying rigorous feature engineering and validation techniques.
• Ability to communicate complex modelling concepts to both technical and non-technical stakeholders.

Nice to Have

• Experience with MLOps, model monitoring, or model governance.
• Exposure to explainable AI techniques such as SHAP.
• Experience within SME, commercial, or retail lending.
• Familiarity with Azure or other cloud platforms.
• Experience working in the GCC or broader MENA financial services market.