Lead the development, validation and optimization of Market & Liquidity Risk models (e.g., interest rate risk, liquidity valuation, VaR models), and design/refine risk metrics and modeling tools to comply with regulatory requirements (e.g., IRRBB, LCR, NSFR) and industry best practices.
Collaborate with project managers, developers and data teams to build and enhance the in-house MLRM system, focusing on modeling modules, risk analytics models, model-driven reporting and supporting data infrastructure.
Partner with local MLRM teams, Treasury and Business divisions to provide modeling expertise, guide local risk modeling initiatives and ensure effective application of model outputs in risk management.
Develop and maintain model-driven regional MLRM dashboards and management reports for senior management and risk committees, ensuring accuracy of model results and risk insights.
Establish and enhance stress testing modeling capabilities, including scenario design, model building, risk vulnerability analysis and mitigation recommendations based on model outcomes.
Assist in reviewing and updating local MLRM policies/procedures related to risk modeling, ensuring alignment with regional framework, regulatory expectations and model governance standards.
Support risk reporting, limit monitoring and advanced analytics using modeling techniques, covering interest rate, liquidity and market risk exposures, and validate model output accuracy.
Assist in formulating and enhancing the regional Market & Liquidity Risk Management (MLRM) framework, focusing on integrating advanced risk modeling methodologies to meet regulatory standards and business needs.
Requirements
Bachelor's degree or above in quantitative fields (Mathematics, Statistics, Engineering, Financial Engineering), with a strong background in risk modeling or quantitative analysis.
At least 3 years of hands-on experience in market/liquidity risk modeling, model development/validation, quantitative risk analytics or treasury risk modeling within a bank/financial institution.
Familiar with MAS regulations and BCBS principles for market/liquidity risk (e.g., IRRBB, LCR, NSFR, stress testing), with deep understanding of model governance and validation requirements.
Strong quantitative modeling skills, with experience in developing, calibrating and validating risk models (e.g., VaR, IRRBB) and interpreting results for stakeholders.
Excellent communication skills, able to collaborate cross-team and convey complex modeling concepts to non-quantitative audiences.
Self-driven, independent, and able to prioritize multiple modeling tasks in a fast-paced environment to meet deadlines.
Proficiency in Python, SQL or VBA, with experience in quantitative modeling, data manipulation and model automation.
Plus: Experience in data analytics, dashboard tools (Power BI, Tableau) for model output visualization, or risk system implementation focusing on modeling modules.
