We are seeking a highly skilled and motivated Credit Risk Modeller to join a team in The Hague with an International Bank. As a Credit Risk Modeller, you will be responsible for developing and maintaining credit risk models that are essential for assessing, monitoring, and mitigating credit risk across the bank's portfolio. Your work will directly impact the bank's decision-making process and contribute to the overall financial health of the institution.
- Develop and implement credit risk models to assess the creditworthiness of individual borrowers, counterparties, and portfolios.
- Analyze credit data, economic indicators, and market trends to inform model development and validation.
- Collaborate with cross-functional teams, including risk management, data analytics, and IT, to ensure seamless integration of credit risk models into the bank's operations.
- Conduct stress testing and scenario analysis to assess the potential impact of adverse economic conditions on the bank's credit portfolio.
- Monitor and validate the performance of existing credit risk models, recommending improvements and updates as necessary.
- Stay up-to-date with regulatory requirements and industry best practices related to credit risk modeling.
- Prepare reports and presentations to communicate model results and insights to senior management and regulatory authorities.
- Master's degree or higher in a quantitative field such as Statistics, Mathematics, Finance, or Economics.
- Strong programming skills in languages like Python, R, or SAS for model development and data analysis.
- Proven experience in credit risk modeling, including scorecard development, PD, LGD, and EAD modeling.
- Knowledge of statistical modeling techniques, machine learning algorithms, and data manipulation.
- Familiarity with banking regulations, particularly Basel III/IV and IFRS 9.
- Excellent problem-solving skills and the ability to work both independently and in a collaborative team environment.
- Strong communication and presentation skills to convey complex concepts to non-technical stakeholders.
- Attention to detail and a commitment to maintaining data integrity and model accuracy.