We are looking for an analytical and detail-oriented professional to join our Provisions Modelling team. The purpose of this role is to ensure accurate and data-driven provisioning across multiple European portfolios in accordance with IFRS 9 standards. The Credit Risk Analyst (Provisions Analyst) will contribute to the development and monitoring of PD, LGD and ECL models, ensure proper provisioning levels, and support business decisions through insightful analysis of portfolio performance across three product lines and twelve countries. This role requires close collaboration with colleagues from Risk, Finance, and other teams to align assumptions, improve model accuracy, and maintain consistent provisioning practices across the Group. Key Responsibilities: Provision Modelling and Monitoring Support the development, monitoring, and enhancement of IFRS 9 models (PD, LGD, ECL). Perform quantitative analyses to assess provision adequacy and trends across portfolios. Portfolio Analytics Analyze portfolio performance across multiple countries and product segments. Identify drivers of changes in provisions and communicate analytical findings clearly. Data Management and Reporting Extract, transform, and validate data from large-scale databases (SQL/Excel). Prepare monthly and quarterly provisioning reports with commentary on key movements. Cross-functional Collaboration Work closely with Finance, Risk, and Modelling teams to ensure consistency in model inputs, assumptions, and outputs. Support coordination of quarter-end provisioning and model update cycles. Documentation and Compliance Maintain transparent documentation of methodology, assumptions, and governance related to IFRS 9 provisions. Support internal and external validation or audit processes. Requirements and Skills: Master’s degree in a quantitative field (Mathematics, Statistics, Economics, Finance, or related). Minimum 2 years of professional experience in credit risk or financial provisioning. Solid understanding of IFRS 9 provisioning concepts (PD, LGD, ECL) and model governance. Strong analytical and problem-solving skills with great attention to detail. Hands-on experience with SQL (querying and transforming large datasets) and Excel (advanced formulas, pivot tables, data visualization). Experience with R or Python for statistical analysis and Power BI for dashboards is an advantage. Fluent in English, both written and spoken, for effective collaboration across countries. Ability to work independently and effectively in a fast-paced, international environment. Competencies and Behaviors: Analytical and detail-oriented: ensures accuracy and quality in data-driven outputs. Proactive and independent: takes ownership of analytical tasks with minimal supervision. Collaborative: works effectively with cross-country and cross-functional teams. Curious and improvement-minded: seeks opportunities to refine processes and enhance model accuracy and efficiency.