Internal Audit Analytics Executive

About the Role

The Internal Audit Analytics Executive plays a key role in driving data-driven internal audit execution. In this role, you will be responsible for extracting, transforming, analyzing, visualizing, and modeling data—including trend analysis and forecasting—to help identify patterns, anomalies, risks, and shifting risk profiles across the organization.

Key Responsibilities:

• Extract, transform, validate, and analyze data from various sources using SQL, Python, or other analytical tools to identify anomalies, transaction patterns, red flags, and high-risk areas.
• Support the design and execution of continuous auditing/continuous monitoring frameworks for key risk indicators (KRIs). Support the development of data analytics tools, automation, and Audit Management Systems.
• Develop and apply trend analysis, forecasting, and predictive analytics to spot potential risk profile changes, project risk indicators, and support early warning systems, risk assessments, and audit planning.
• Validate the quality, completeness, consistency, and integrity of data used in audit testing and analysis.
• Maintain detailed, systematic documentation of queries, scripts, analytical methodologies, parameters, and findings to ensure repeatability and auditability. Keep existing analytics rules, queries, dashboards, and automated tests updated inline with evolving business processes and risk profiles.
• Partner with internal auditors and business units to translate business risks into data analytics procedures. Conduct preliminary investigations into identified exceptions and present actionable findings to the Senior Manager and audit teams.

About You:

We are looking for an analytical thinker who can bridge the gap between complex data analysis and internal control/risk management goals.

Required Qualifications & Skills:

• Bachelor’s Degree (S1) in Statistics, Information Technology / Information Systems, Computer Science, Data Science, or a related field.
• Minimum 3 to 5 years of hands-on experience in Data Analytics, Audit Analytics, Internal Audit, Risk Analytics, Fraud Analytics, or Business Intelligence.
• Experience in Banking or Financial Services is highly preferred.
• Strong mastery of SQL for data extraction, transformation, and validation.
• Practical experience with Python or other analytical programming languages is a strong plus.
• Hands-on experience with data visualization tools such as Power BI, Tableau, Looker , or similar software.
• Prior experience using an Audit Management System is a plus.
• Fundamental understanding of internal audit concepts, governance, internal controls, risk management, and banking business processes.
• Sharp analytical mindset with strong problem-solving skills and an ability to spot anomalies and exceptions in complex datasets.
• Systematic approach to documenting technical processes and analysis results.
• Excellent communication skills, with the ability to translate technical data insights into clear, actionable findings for non-technical stakeholders.