• Define and own the multi-year AI and analytics roadmap for Internal Audit, aligning it with ADM's broader enterprise data strategy.
• Lead the end-to-end deployment of AI agents across the audit lifecycle - risk assessment, scoping, fieldwork, testing, reporting, and issue follow-up.
• Identify and prioritize high-value opportunities to automate manual, repetitive audit procedures through intelligent agents and robotic process automation (RPA).
• Partner with ADM's enterprise AI, data engineering, and IT teams to access data assets and integrate audit tooling into the broader technology stack.
• Evaluate and implement best-in-class audit technology platforms, AI co-pilot tools, and large language model (LLM) applications relevant to internal audit.

• Re-engineer core audit processes to operate in an AI-augmented environment - redesigning workflows, control testing approaches, and documentation standards.
• Establish a continuous auditing and continuous monitoring (CA/CM) capability, enabling real-time risk signals and always-on audit coverage across critical processes.
• Develop and maintain a suite of reusable analytics tools, data models, and automated testing scripts that audit teams can deploy across engagements.
• Drive standardization of data ingestion, transformation, and analysis pipelines to ensure consistency, auditability, and scalability.

• Design and lead a structured analytics and AI upskilling program for the full Internal Audit team - spanning foundational data literacy through advanced AI fluency.
• Create a tiered competency framework aligned to roles (Staff Auditor through Assistant Director), with targeted learning paths, hands-on labs, and applied project experience.
• Embed analytics specialists alongside traditional audit teams on engagements, creating a "BIE-style" model where data capabilities are integrated into every project.
• Champion a culture of curiosity, experimentation, and continuous learning; recognize and reward innovation by team members.
• Serve as the internal center of excellence for analytics and AI - coaching teams, fielding questions, and building institutional knowledge.

• Lead and oversee data-driven audit engagements, applying advanced analytics to evaluate controls, detect anomalies, and surface insights not visible through traditional sampling.
• Incorporate AI-generated risk signals into the annual audit plan and dynamic risk assessment process; provide the CAE with data-backed perspective on emerging risks.
• Ensure appropriate governance, bias controls, and explainability standards are applied when AI outputs inform audit conclusions.
• Prepare and present executive-ready deliverables - translating complex analytical findings into clear narratives for the Audit Committee, CFO, and senior management.

• Build trusted relationships with ADM's CFO, Controller, Chief Data Officer, and CIO organizations to align on data access, AI initiatives, and joint priorities.
• Represent Internal Audit in enterprise-wide AI governance forums; contribute to responsible AI policy and ethical use standards.
• Coordinate with external auditors on data analytics methodologies to ensure alignment and avoid duplication of effort.

• Bachelor's degree in Accounting, Finance, Data Science, Computer Science, or a related field; advanced degree preferred.
• CPA, CIA, or CISA strongly preferred; data-related certifications (e.g., AWS, Azure, Google Cloud, Databricks) a plus.

• 12+ years of progressive experience across internal audit, external audit (Big 4), or data/analytics roles within a large, complex organization.
• Demonstrated track record designing and deploying AI or advanced analytics solutions in an audit, risk, finance, or compliance context.
• Experience leading or significantly contributing to digital transformation or process automation initiatives.
• Prior people leadership experience with a passion for coaching, developing, and retaining talent.
• Experience in product ownership or familiarity/certification in agile methods and frameworks

• Proficiency in analytics and data platforms: Python, SQL, Power BI, Tableau, Alteryx, or equivalent.
• Working knowledge of AI/ML frameworks and generative AI concepts (LLMs, prompt engineering, agentic architectures, RAG).
• Familiarity with cloud data environments (Azure, AWS, Snowflake, Databricks) and data governance principles.
• Experience with ERP systems and audit management platforms.
• Strong command of Microsoft 365 productivity suite including Power Automate, Copilot, and Excel.

• Exceptional executive presence - able to communicate complex analytical and technical content to non-technical audiences including the Audit Committee and C-suite.
• Strategic thinker who can translate ambiguous organizational goals into executable roadmaps and measurable outcomes.
• Collaborative influencer skilled at building consensus across functions, geographies, and seniority levels.
• High degree of intellectual curiosity and comfort operating in rapidly evolving, ambiguous environments.

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