Job Description
The Internal Audit Analytics Lead supports the advancement of the Internal Audit function’s data, analytics, and AI capabilities through execution, enablement, and integration into audit activities.
This role serves as a hands-on lead and subject matter resource, focused on embedding data-driven testing, enhancing continuous monitoring and risk assessment, and strengthening issue validation through both analytics and substantive testing. The position partners with audit teams, Technology, and Risk functions to improve audit coverage, efficiency, and insight generation.
Essential Duties and Responsibilities
- Serve as the department’s analytics subject matter expert and propose solutions for auditing challenges
- Develop and implement a data analytics program to support audit testing, including full-population testing, exception identification, trend analysis, and potentially visualization if needed to support reporting
- Partner with audit teams to integrate data analytics throughout the audit lifecycle, increase the use of data-driven assurance techniques, and improve audit efficiency and effectiveness.
- Apply AI-enabled and advanced analytics tools, where appropriate, in alignment with bank policy and governance expectations
- Monitor emerging analytics, automation, and AI technologies and collaborate with the Internal Audit leadership on applicability
- Collaborate with Data Owners, Stewards, and Custodians to obtain, understand, and validate data sources used in audit analytics
- Acquire, transform, and analyze data from disparate source systems; document methodology, logic, and evidence in accordance with audit workpaper and GIAS documentation standards
- Develop and execute continuous monitoring routines using data analytics and prepare monitoring outputs and dashboards
- Support risk assessment activities through development and use of data-driven risk indicators and monitoring insights
- Support issue validation activities using both:
- Data analytics techniques (e.g., automated testing, population analysis)
- Substantive testing (e.g., control design and operating effectiveness testing)
- Combine analytics-based and traditional testing approaches to ensure validation is risk-aligned, comprehensive, and well-documented
- Partner with audit teams and issue owners to develop repeatable and consistent validation approaches
- Assist in integrating analytics-enabled testing approaches into audit methodology and guidance, ensuring alignment with enterprise data governance standards, authorized tools, and the bank's data management capability model.
- Deliver training and coach auditors on analytics tools, techniques, and interpretation of results
- Participate in working groups or forums related to data, analytics, or AI, representing Internal Audit as needed
- Support other departmental initiatives and responsibilities as assigned
Education and/or Experience:
- Bachelor’s degree in Data Analytics, Information Systems, Computer Science, Statistics, or related field
- 5–7 years of experience in data analytics, internal audit analytics, or data-driven risk/control functions
- Experience within a regulated financial institution is beneficial but not required
Skills and Abilities
- Strong capability in data extraction, transformation, and analysis
- Proficiency in analytics and visualization tools (e.g., SQL, Python, Power BI, Microsoft Fabric, Tableau, Alteryx, or similar)
- Understanding of data governance and data quality considerations
- Ability to translate business risks into analytic procedures and actionable insights
- Ability to apply professional skepticism to analytical results and evaluate whether exceptions represent control failures.
- Strong communication skills with the ability to explain technical concepts clearly
- Ability to manage multiple priorities and deliver high-quality, reproducible work
- Ability to demonstrate the highest level of ethical behavior and maintain confidentiality with sensitive information.
