Senior Credit Risk Modelling Analyst

Support the end-to-end development and implementation of credit risk models (PD, LGD, EAD)

Support the back testing for IFRS9 (PD, LGD, EAD, SICR) and statistical forward-looking Models.

Parameter Estimates for IFRS9 to ensure that the models are running as expected.

Monitor the performance of the models and implement controls that help to prevent data quality issues affecting the models.

Participate to the constant improvement of the models, propose new potential segments to target, comply with the evolution of the regulation and create or improve the documentation where necessary.

Experience and Skills

• Experience with External Audit is essential.
• Stay updated on industry trends, regulatory changes, and best practices in credit risk modelling to ensure the company's policies remain current and effective.
• Prepare high-quality, detailed model documentation, implementation reports, and performance monitoring presentations for a range of audiences, including senior management, internal audit, and regulatory bodies.
• Adequate knowledge with machine learning techniques (e.g., Gradient Boosting, Random Forests, deep Neural Networks) and their application in a credit risk context is desirable.

Education and Skills

• Strong academic background with a degree in a quantitative discipline such as Statistics, Mathematics, Economics, Physics, or Engineering.
• Detailed understanding of the underlying statistical theory is essential.
• Significant experience in proactively problem solving and analysing of large, complex data sets, identify trends, and make data-driven decisions.
• Advanced and demonstrable programming skills in SAS are mandatory for this role.
• Proficiency in at least one other statistical programming language, such as Python or R.
• Ability to work under pressure and with short deadlines.
• Strong communication skills, with the ability to articulate complex technical concepts to non-specialist audiences, both orally and in written form.