Senior Data Scientist [Credit Risk - Dubai]

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 bank, digital bank, fintech, 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.