Independently own end-to-end risk data analytics and full lifecycle risk data asset validation. Lead the assessment of data accuracy, integrity, consistency and structural data risks. Identify systemic data quality issues, conduct root-cause analysis, and drive cross-team remediation and long-term data standardization improvements.
Lead and oversee enterprise risk monitoring and compliance reporting frameworks. Own the design, stabilization, and continuous optimization of recurring risk tasks, control monitoring outputs, compliance logs, and periodic risk operation reports to support internal review, management oversight, internal audit and compliance evidence requests. Provide stable cross-functional data and risk support for Compliance, Internal Audit, Business, and IT Governance teams. Respond to recurring and ad-hoc data inquiries, audit evidence requests, and compliance validation needs, ensuring all risk and AI governance deliverables are well-documented, explainable, and fully auditable. Take full ownership of the company’s internal fraud program and employee misconduct detection mechanism. Lead advanced behavioral and transactional risk analysis, identify complex, hidden internal risk patterns, conduct trend governance, and deliver high-confidence risk findings for investigation and control enhancement. Partner closely with compliance, internal audit, technology, and business leadership to provide senior-level data insights, validate control effectiveness, and support formal audit review and governance reviews. Support ad-hoc advanced analytics and AI-related tasks upon team request (non-core responsibility). Assist in statistical analysis, model validation, and analytical enhancement projects as supplementary capacity when needed. Serve as the data owner for enterprise AI Governance oversight. Independently conduct AI model data validation, algorithm fairness monitoring, model drift detection, AI access & behavior audit, and AI compliance risk assessment. Establish AI risk logs, govern AI operational control quality, and drive continuous AI governance maturity improvements. Lead structured risk post-mortem, conduct in-depth causal analysis for complex risk incidents, data control failures, and AI governance gaps. Summarize systemic risk weaknesses, refine risk rule sets, control standards, and governance best practices to proactively mitigate enterprise-level risks. Provide senior ad-hoc advanced analytics support for critical risk initiatives, model validation projects, and AI governance enhancement tasks as required. Standardize team SOPs, govern risk data quality standards, and continuously mature the overall risk and AI data governance framework.