Senior Risk Model Validator
2 weeks ago
A senior-level professional is sought after to assume responsibility for validating credit risk models within the context of Singapore's expanding digital banking landscape.
The ideal candidate will possess a strong understanding of regional regulatory requirements and be able to develop and maintain model risk policies that ensure compliance with industry guidelines.
In this role, you will lead the consistency of model risk management across different countries and oversee the end-to-end management of the model lifecycle.
You will be responsible for managing model risk reports for stakeholders and regulators, as well as putting in place AIDA model risk management frameworks and processes.
This position requires a good understanding of quantitative finance and statistical modeling techniques, proficiency in programming languages such as Python, R, or SAS, and effective stakeholder management skills.
Key Responsibilities:- Develop and own regional model risk policies and guidelines, ensuring they remain compliant with all relevant industry and regulatory guidelines.
- Lead the consistency of model risk management policies, guidelines, and processes across different countries.
- Responsible for the end-to-end management of the model lifecycle, ensuring compliance with the bank's policies and guidelines.
- Manage model risk management reports for stakeholders and regulators.
- Put in place AIDA model risk management framework and processes.
- Bachelor's Degree or higher in a Quantitative field (e.g. financial engineering, mathematics, statistics, or related field) from a recognized University.
- 7-10 years of relevant experience working with Risk Management, Model Development, Model Monitoring, Model Validation, or related fields.
- Relevant experience with Credit Risk Model development and/or Credit Risk Model Validation in Retail/Consumer Banking is highly preferred.
- CFA, FRM, or any other relevant certifications.
- Strong understanding of regulatory compliance requirements related to model risk.
- Strong understanding of quantitative finance and statistical modeling techniques.
- Proficiency in programming languages (i.e. Python, R, SAS).
- Effective stakeholder management and communication skills, strong problem-solving skills.
- Good team player and strong stakeholder management skills.
- Strong written and verbal communication skills.
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