My client is seeking a number of credit risk modelling specialists for a large project designing, building & implementing credit risk models. Ideally you will have experience of Retail Banking / Commercial Banking or Corporate Banking.
Below are some of the responsibilities you will have in this role:
- Contribute to all aspects of credit risk model development and deployment including coding, testing, validation and review. The most common types of credit risk models worked on by the team are operational scorecards, capital models, impairment models, forecasting models and stress testing models.
- Help deliver projects to evaluate, design, develop and implement policies, procedures and strategies to effectively deploy and execute credit risk models and processes, consistent with regulatory requirements and/or market practice across credit risk model delivery.
- Perform reviews of credit risk model deployment and execution frameworks, including gathering business requirements, assessing conceptual designs, examining governance and controls, and testing outcomes.
The ideal candidate will have the following experience:
- Numerical degree e.g. Mathematics, Engineering, Physics, Operational Research, Computer Science
- Masters degree in a relevant quantitative/finance discipline or Professional qualification (such as PRMIA, GARP, CFA) an advantage
- Strong work ethic, professional and personable
- High personal standards with respect to the quality of your own work
- The ability to work seamlessly as part of a wider team, furthering common goals and working within demanding deadlines
- Experience of the credit risk management and delivery software available in the market which is used for credit risk management and model execution across the customer lifecycle.
- Credit risk management, credit risk modelling or business expertise within a Retail/Commercial or Corporate bank, with the ability to apply technical financial services regulation to practical business scenarios
- Interpersonal and influencing skills, including strong oral and written communication of technical concepts to a non-technical audience
- Strong IT skills including Microsoft applications (Word, Excel, PowerPoint) and statistical packages (e.g. SAS)