A leading bank is looking to build out their commercial credit risk modeling team in their Tampa, FL office. They are looking for strong candidates with experience in model development and credit risk analytics. They are primarily looking for candidates who have experience modeling PD, LGD, and EAD ratios as well as economic capital modeling and ideally have experience with stress testing.
1. Work with senior quants developing or enhancing Risk Capital/Stress Testing models for wholesale credit risk (HFI, HFS, AFS, HTM, etc. exposures)
2. Develop PD/LGD/EAD/correlation/rating transition model to measure risk capital (economic capital), assess concentration risk, allocate risk capital or stress loss to lower business level or transaction level
- Develop risk capital model for securitization exposure
4. Implement model analytics, model libraries/engine/executables and associated analytical tools, using programming languages such as C++, Python, VBA
5. Test model performance, implement testing suites for new and existing models, establish automated testing processes and repeated model documentation processes
- Assist testing efforts and support requirements from Model Risk Management, participate in full model development, validation and ongoing performance monitoring cycles
- Partner with Risk Reporting and IT to ensure that Risk Capital enhancements are correctly implemented and integrated in risk and finance systems
1. Masters and above degree in a quantitative discipline such as mathematics, financial engineering, physics, statistics, computer science, etc.
2. 5+ years of experience in an analytics, quantitative programming and implementation roles in a financial institution
3. Knowledgeable about risk measurement issues in wholesale credit risk, default correlation, concentration risk necessary
- Knowledge of wholesale CCAR PD/LGD/EAD models and knowledge about wholesale CECL a plus
5. Knowledge of risk capital and stress testing concepts and issues a plus
6. Strong communicator, self-starter, and team player.
7. Eagerness & ability to grasp complex analytical or mathematical concepts quickly.
- Proficient in C++/C, Python, Excel VBA, Java and/or other programming languages.
9. Experience with model implementation and integration with technology systems.
10. Ability to navigate through complex data and infrastructure environment a plus.
11. Experience with implementing analytical user tools such as what-if calculator in Excel or other UI form a plus.
12. Experience with database, cloud computing, client-server computing, distributed computing a plus.
13. Exceptional candidates who do not meet all these criteria may be considered for the role provided they have the necessary skills and experience.