Responsibilities
- Work closely with Credit Risk Modellers and IT team to implement IFRS9 ECL models and stress testing methodologies.
- Communicate model requirements with IT team for the deployment of models.
- Validate and test model implementations, ensuring accuracy and alignment with model design.
- Collaborate with Modellers to gather feedback and address any issues during model deployment.
- Monitor model results calculated by the system, identify /raise / fix / track potential system defects and or deficiencies.
- Collaborate with IT team on system soundness and efficiency.
- Provide training and support to in-team junior members on model implementation, change request maintenance and defects identification & fixing.
- Participate in model governance activities, including system related documentation and reporting.
Requirements
- Bachelors degree in Finance, Economics, Statistics, Computer Science, or a related field.
- At least 5 years of experience in credit risk analysis, risk modelling, risk system implementation, or related roles.
- Strong knowledge of Moodys RCO product and/or IFRS9 ECL models
- Proficiency in statistical software (e.g., SAS, R, Python, SQL) or Oracle DB for model implementation
- Excellent analytical skills and attention to detail
- Effective communication abilities
- Relevant certifications (e.g. FRM, CFA) are a plus.
Please apply online via the BEA Careers website at https://careers.hkbea.com/psp/hcmprd/EMPLOYEE/HRMS/c/HRS_HRAM.HRS_APP_SCHJOB.GBL?Page=HRS_APP_JBPST&Action=UFOCUS=Applicant&SiteId=1&JobOpeningId=4541&PostingSeq=1 or by clicking the "Apply Now" button below. Kindly note that if you are a new user, you have to first create your User Profile before you can apply.
Personal data provided by job applicants will be used for recruitment purposes only and will be treated in accordance with the Bank's Personal Information Collection (Employees) Statement and Privacy Policy Statement. Applicants who are not invited for interviews within six weeks may consider their applications unsuccessful and the personal data collected will be destroyed after 1 year.