Digital Data & AI Internal Audit Lead

Job Description Digital Data & AI Internal Audit LeadPackage: 80,000120,000 + 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 firms 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 & ExperienceHands-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.

Created: 2025-11-29