Senior Model Risk Specialist

GXS Group; Singapore; On-site; SGD 140,000 - 200,000; Full time

Job summary

GXS Group in Singapore seeks a skilled Model Risk Manager to join the Bank's Second Line of Defense within Risk Management. You will oversee independent validation, governance, risk assessment and advisory support for traditional and AI models across the bank.

You will collaborate with model owners and analytics teams to remediate findings, drive automation, and strengthen the model risk culture while aligning with MAS and other regulatory guidelines.

Qualifications

• Degree in a quantitative field or equivalent banking model risk experience.
• Postgraduate, CFA and/or FRM qualifications are an advantage.
• Strong knowledge of modeling/validation techniques for traditional and AI models.
• Familiar with AI governance landscape and regulatory guidance (BNM, MAS).
• Ability to assess AI/ML risks such as explainability and drift.
• Excellent communication and stakeholder management skills.

Responsibilities

• Manage end-to-end model lifecycle for new and existing models across the Bank.
• Perform independent validation of risk models including scorecards, IRB, ECL, AML, Fraud.
• Assess model risk for AI use cases including FEAT assessments and AI-specific risk assessment.
• Review model documentation, test implementations, and assess performance during reviews.
• Ensure model risk controls are embedded across the lifecycle.
• Maintain and enhance model risk frameworks, policies, and standards per regulatory requirements.
• Provide advisory support on model risk governance and best practices.
• Drive automation, process harmonisation, and data standardisation in model governance.
• Communicate model risk findings and validation outcomes to stakeholders and senior management.
• Work with model owners, developers, and quantitative analysts to remediate findings.

Skills

Model risk management

Validation techniques

AI governance

Regulatory guidance

Communication

Education

Quantitative field degree

CFA/FRM qualifications

Tools

Model validation tools

Job description

The role sits in the Model Risk Management Team. This is a Second Line of Defense role in the Risk Management function. The role is responsible for managing the model risk management activities across the Bank through independent model validation, governance, risk assessment, and advisory support covering traditional and AI models.

Job Responsibilities:

• Manage the end-to-end model lifecycle for new and existing models across the Bank.
• Perform independent validation of risk models, including scorecards, IRB, ECL, AML, Fraud and other models.
• Assess model risk for AI use cases, including FEAT assessments and/or AI-specific risk assessment, in line with industry best practices or regulatory guidelines.
• Review model documentation, test model implementation, and assess model performance through ongoing and annual reviews.
• Ensure model risk controls are embedded across the model lifecycle.
• Maintain and enhance model risk frameworks, policies, and standards in line with regulatory requirements.
• Provide advisory support on model risk governance and best practices.
• Drive automation, process harmonisation, and data standardisation in model governance.
• Communicate model risk findings and validation outcomes to stakeholders and senior management.
• Work with model owners, developers, and quantitative analysts to remediate findings and strengthen model risk culture.

Requirements:

• Degree in a quantitative field such as Statistics, Mathematics, Actuarial Science, Data Science, Economics, Finance, Engineering, or a related field; or with relevant experience in model risk management, validation, or model governance in banking.
• Postgraduate, CFA and/or FRM qualifications are an advantage.
• Strong knowledge of modeling and validation techniques for both traditional and AI models.
• Familiar with model/AI lifecycle controls.
• Familiarity with AI Governance landscape and have good understanding of relevant regulatory and industry guidance, including BNM and MAS expectations on emerging AI governance standards.
• Ability to independently assess AI/ML risks such as explainability, fairness, robustness, and model drift.
• Strong communication, stakeholder management, and collaboration skills, with exposure to automation and governance process improvement.

We live in a fast-paced, highly interconnected world. Technology has transformed the way we live, work, bank and pay. We want to revolutionise banking as we know it today, by leveraging the extensive ecosystems, technology expertise and fintech experiences of our parent companies, Grab and Singtel, to serve everyday consumers and small businesses better.