Digital Data & AI Internal Audit Lead

Digital Data & AI Internal Audit Lead

Package: £80,000–£120,000 + bonus + LTIP + hybrid working (London) + visa sponsorship available.

Our financial services client is seeking a Digital Data & AI Internal Audit Lead to strengthen their AI-driven assurance capability. You will lead the design and delivery of AI automation , data risk assurance , and advanced analytics audits , while also supporting a portfolio of Tier 1 banking clients undergoing major data and cloud transformation programmes.

This role combines deep data/AI governance expertise , internal audit delivery , and practical automation engineering , enabling you to shape how AI is safely and effectively embedded into assurance processes.

• Deliver and lead complex data management, AI assurance, and analytics audit - including evaluating model risk controls, AI system governance, data pipelines, and cloud-based data platforms.
• Build and enhance AI-enabled audit methodologies , using automation and continuous monitoring techniques (e.g., anomaly detection, NLP, predictive analytics) to improve audit depth and efficiency.
• Develop and implement data and AI governance frameworks for clients, including standards for data quality, lineage, metadata, responsible AI, and regulatory compliance (e.g., PRA, FCA, EU AI Act).
• Assess compliance with data and AI controls , validating technical design, operational processes, and end-to-end data lifecycle management.
• Support practice growth , helping expand the firm’s Data & AI Internal Audit offering and designing new propositions aligned to emerging AI risks and regulatory expectations.
• Drive business development - building trusted relationships with senior banking stakeholders and supporting proposal writing, scoping workshops, and solution design.

Essential Skills & Experience

• Hands-on experience delivering data management, analytics, or AI assurance audits within internal audit, Big 4, consulting environments or Financial Services (mandatory).
• Strong internal audit experience , with the ability to design AI-enabled audit workflows, automated testing scripts, and continuous monitoring controls.
• Expert knowledge of data governance and controls , including data quality rules, lineage tracking, metadata standards, and platform-level risk management.
• Deep understanding of AI assurance, including model governance, algorithmic transparency,
• Technical experience with data and AI platforms: Snowflake, Databricks, Microsoft Purview, Collibra, Informatica, AWS, Azure, or similar.
• Proficiency with analytics tooling: SQL, Python, Alteryx, Tableau, Power BI, or other BI/ETL tools.