Title: Risk Analytics Manager Duration: Y/E 2026 renewable contract Salary: HKD60,000 per month (depending on experience) Role purpose Deliver project-based credit risk analytics and end-to-end model development, supporting delivery from requirements and data preparation through build, testing, implementation, and handover. The role also supports UAT and production of clear risk insights to ensure model and reporting changes are accurate, controlled, and ready for business use.
Key responsibilities Credit risk analytics, modelling & project delivery - Deliver project-based credit risk analytics and modelling work to agreed scope, timelines, and quality standards.
- Work with stakeholders to clarify requirements, define deliverables, and translate needs into analytical/model specifications.
- Prepare and analyse data to support portfolio insights and model development (including data quality checks and reconciliations).
- Develop end-to-end credit risk models as required by the project, including build, testing, implementation support, and handover.
- Develop alternative/benchmark (challenger) models where needed to support comparison and confidence in outcomes.
- Produce clear outputs for stakeholders (e.g., analysis summaries, model results, and key assumptions/limitations) to support decision-making.
- Maintain appropriate project documentation and evidence to support governance, auditability, and smooth transition to BAU teams.
UAT (User Acceptance Testing) - Plan and execute UAT for models/data/reporting changes, including test data, expected results, defect management, and re-testing.
- Perform key control checks and maintain evidence to support sign-off and auditability.
- Work with Credit Risk, Finance, Technology, and Data teams to align scope, timelines, and dependencies.
- Provide regular updates, support governance routines, and coordinate reviews to enable smooth delivery and handover.
Skills and experience (essential) - Project-based experience in credit risk analytics and/or end-to-end model development within financial services.
- Strong data and analytics skills (SQL, Excel, and Python/R/SAS or similar).
- Good credit risk knowledge (e.g., PD/LGD/EAD, ECL, portfolio performance metrics).
- Hands-on UAT experience and strong communication skills; able to deliver at pace.
Skills and experience (desirable) - Exposure to regulatory and financial risk modelling use cases.
- Experience building benchmark/challenger models or performing model performance checks.
- Familiarity with governance expectations in regulated environments (documentation, controls, audit trail).
- Experience working with Technology/Data teams on implementation and release activities.
- Experience with Agile delivery tools and ways of working (e.g., Jira/Confluence).
