דרושים Model Risk Management Lead בתל אביב

We are looking for an experienced professional to lead and oversee the bank’s Model Risk Management (MRM) framework as part of the Second Line of Defense. In this role, you will ensure that the development, implementation, usage, and validation of all models across the organization meet regulatory expectations, internal governance standards, and our overall risk appetite. This is an opportunity to own an enterprise-level domain with visibility across the bank’s most critical analytical and decision-making processes.

Your Day-to-Day:

• Establish, maintain, and enforce the bank’s Model Risk Management policies and procedures.
• Implement model validation methodologies and best practices.
• Develop and maintain the enterprise Model Inventory, including model identification, documentation, classification, version control, and risk assessments.
• Conduct thorough validation of financial, regulatory, predictive, and LLM-based models, as well as vendor and third-party models, ensuring accuracy and effectiveness.
• Work with cross-functional teams to present insights and recommendations for model and process enhancements.
• Document validation processes and results while ensuring transparency and compliance with regulatory standards.
• Independently monitor, measure, and assess model risk at individual-model and portfolio levels, identifying opportunities for improvement.
• Report material model risks, findings, and remediation recommendations to senior management.
• Participate in the review of new products or significant model changes and evaluate their impact on model risk and compliance requirements.

Requirements:

• Bachelor’s or Master’s degree in a quantitative field (Mathematics, Statistics, Finance, or related discipline).
• 5+ years of experience in Model Risk Management, Model Validation, Quantitative Risk, Internal Audit, or similar roles in the financial/banking sector.
• Strong analytical and problem-solving abilities, with attention to detail and the capability to independently manage complex review processes.
• Deep understanding of quantitative modeling techniques: statistical methods, econometric models, financial modeling, machine-learning concepts, and back-testing.
• Familiarity with Model Governance frameworks, internal control structures, and regulatory expectations for model risk.
• Knowledge of SQL and hands-on experience querying databases.