Lead Assistant Manager

We are seeking a highly skilled and motivated Credit Risk Analyst to join our dynamic Risk Management team. The ideal candidate will play a critical role in developing, executing, and refining credit risk stress testing models and frameworks to ensure that the organization is well-positioned to manage and mitigate credit risk under various economic and financial scenarios. Key Responsibilities Credit Risk Stress Testing: Develop and execute stress testing frameworks to assess credit portfolio vulnerabilities under adverse scenarios. This includes scenario design, data collection, model execution, and result interpretation. Model Development: Collaborate with risk modeling teams to enhance stress testing models, including probability of default (PD), loss given default (LGD), and exposure at default (EAD) models. Regulatory Compliance: Ensure compliance with regulatory requirements for stress testing, including those prescribed by the Federal Reserve, HKMA, Basel guidelines, and other regulatory bodies. Data Analysis & Reporting: Analyze large datasets to identify trends, risks, and performance gaps. Provide insights through detailed reports to senior management and other stakeholders. Scenario Analysis: Create customized stress scenarios for specific market and credit risk factors such as changes in interest rates, unemployment, or housing market conditions. Documentation & Validation: Maintain thorough documentation of stress testing methodologies and validation efforts for both internal and regulatory audits. Qualifications Educational Background: Bachelor’s degree in Finance, Economics, Mathematics, Statistics, or a related field. Master’s degree or professional certifications such as CFA, FRM, or PRM are preferred. Experience: 1-4 years of experience in credit risk management, stress testing, or financial modeling, preferably in the banking or financial services sector. Hands-on experience with regulatory stress testing frameworks (CCAR, DFAST, CECL) is highly desirable. Technical Skills: Proficiency in statistical and data analysis software (e.g., SAS, SQL). Strong knowledge of credit risk modeling, including PD, LGD, and EAD frameworks. Experience with SQL and other data querying tools is a plus. Regulatory Knowledge: Familiarity with global regulatory requirements (e.g., Basel III, IFRS 9, HKMA, MAS, CCAR, CECL ) related to credit risk stress testing. Show more Show less