Market & Liquidity Risk Modelling Specialist - Digital Banking
ShopeeWhat you'll do
● Lead the development and optimization of Market & Liquidity Risk models (e.g., pricing, IRRBB, liquidity risk, stress testing, and 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, market & liquidity risk managers and Risk Data teams to build and enhance the in-house MLRM system
● Partner with local MLRM teams, Treasury and Business divisions to provide modeling solutions, guide local risk modeling initiatives and ensure consistent modeling approach across different countries.
● Assist in developing and maintaining 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 model risk management policies/procedures related to Market and Liquidity risk modeling, ensuring alignment with regional framework, regulatory expectations and model governance standards.
- Support model risk reporting to senior management and model committee
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 IRRBB 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.