Audit Analytics & AI Auditor

Job Description

The Audit Analytics & AI Auditor is responsible for embedding data analytics, automation and responsible AI capabilities within the Internal Audit & Compliance function, enabling a shift from traditional sample-based testing toward full-population, continuous assurance. The role designs, builds and maintains exception dashboards, risk-sensing analytics and automated testing routines that strengthen the Group’s ability to detect payment, vendor and leakage risks in real time, while piloting responsible AI use cases and embedding sound governance over their use. Working closely with the Director – Internal Audit, Senior Compliance Manager and audit engagement teams, the role bridges audit methodology and data science to deliver faster, deeper and more consistent assurance across OMNIYAT Group.

Day-to-Day Tasks:

1. Build, test and maintain analytics-enabled audit routines, exception dashboards and continuous monitoring scripts that flag control breaches and anomalies on an ongoing basis
2. Develop and refine risk-sensing analytics covering payments, vendor activity, procurement and leakage indicators to support early detection of irregularities
3. Automate recurring audit and compliance tests, and maintain, version-control and troubleshoot the underlying data pipelines and scripts
4. Provide data extraction, cleansing, reconciliation and analysis support to internal audit, compliance and project audit engagements across the Group
5. Run responsible AI pilots within the function, documenting use cases, outcomes, limitations and governance considerations for review by senior stakeholders
6. Maintain and enhance CAO/Chairman insight dashboards, ensuring data accuracy, timely refresh and clear presentation of key metrics
7. Partner with Assistant Managers and Auditors to design, build and execute analytics-based testing that supports audit engagement objectives
8. Coordinate with IT & Digital Security and Enterprise Technology on secure data access, system integrations and change requests affecting analytics tools
9. Design data models, algorithms and scripts that support full-population testing across priority risk areas, replacing sample-based approaches where feasible
10. Validate the accuracy, completeness and integrity of analytics outputs prior to their use in audit conclusions or management reporting
11. Support the Director – Internal Audit in profiling emerging technology, data and AI-related risks across the Group’s operations
12. Document analytics methodologies, assumptions and logic, and maintain a reusable script and testing library for the function
13. Deliver training and knowledge-sharing sessions to Internal Audit and Compliance colleagues on analytics tools, dashboards and interpretation of results
14. Present analytics insights, dashboard outputs and audit findings clearly to non-technical stakeholders, including senior management where required
15. Monitor emerging data analytics, automation and AI tools and technologies, and recommend enhancements to the function’s analytics capability and roadmap

Long Term Projects

• Drive the function’s transition to full-population, continuous assurance across priority audit areas.
• Establish a responsible AI governance approach for audit and compliance analytics.
• Expand the exception-dashboard suite to cover additional risk domains group-wide.

Experience and Qualification:

• Bachelor’s degree in Data Science, Information Technology, Computer Science, Accounting or a related field. A data analytics or audit technology certification is an advantage.
• 5+ years of experience in audit analytics, data analytics or technology-enabled assurance.
• Data analytics and visualization platforms (e.g. ACL, Power BI, SQL/Python)
• Design of exception dashboards and continuous monitoring routines
• Risk-sensing analytics covering payments, vendor activity and leakage indicators
• Test automation for recurring audit and compliance procedures
• Responsible AI piloting, documentation and governance
• Data extraction, cleansing and reconciliation across ERP and business systems
• Presentation of analytics insight to non-technical stakeholders