Director - Data Analytics & Artificial Intelligence Audit

Qualifications

• 10+ years of experience in Internal Audit, or related roles within a large financial institution, consulting firm, or regulator
• Deep understanding of data analytics platforms, AI/ML models, and modern data architectures
• Strong knowledge of model risk management, governance frameworks, and control design
• Proven experience leading large, complex audits and managing senior-level stakeholders
• Ability to interpret regulatory guidance related to model risk, data governance, and emerging technologies

Benefits

• Opportunity to shape the firm’s approach to AI, analytics, and emerging technology risk
• Competitive compensation and long-term career growth within a global investment bank

Responsibilities

• The Director of Data Analytics & Artificial Intelligence Audit will lead the design, execution, and evolution of audit coverage for advanced analytics, machine learning, artificial intelligence, and data governance across a global investment banking platform
• This role sits at the intersection of internal audit, technology risk, model risk management, and regulatory compliance, serving as a trusted advisor to senior management, regulators, and audit committees
• The successful candidate will bring a strong foundation in internal audit and risk management while demonstrating deep fluency in data architecture, analytics platforms, AI/ML models, and emerging technologies used across trading, risk, compliance, finance, and operations
• Audit Strategy & Leadership
• Own and evolve the audit strategy for data analytics, artificial intelligence, machine learning, and advanced model usage across the enterprise
• Lead complex, global audits covering AI/ML models, automated decisioning, algorithmic processes, data pipelines, and analytics platforms
• Assess governance, controls, and risk management practices related to data quality, model lifecycle management, explainability, bias, and ethical AI
• AI, Analytics & Model Risk Coverage
• Evaluate the design and effectiveness of controls across the full AI/ML lifecycle, including data sourcing, feature engineering, model development, validation, deployment, monitoring, and decommissioning
• Partner closely with Model Risk Management, Technology Risk, Cybersecurity, and Compliance teams to ensure aligned risk coverage
• Review usage of AI and analytics within front office, risk, finance, compliance, AML, operations, and corporate functions
• Regulatory & Governance Oversight
• Assess compliance with global regulatory expectations related to model risk, data governance, privacy, and AI oversight
• Support regulatory examinations and inquiries related to analytics, models, and AI usage
• Present audit findings and risk themes to senior management, risk committees, and audit committees
• Lead, mentor, and develop a team of audit professionals with analytics, technology, and quantitative skill sets
• Drive the use of data analytics and continuous auditing techniques within the Internal Audit function
• Influence the broader audit organization’s adoption of advanced analytics and AI-enabled audit methodologies
• Stakeholder Engagement
• Serve as a senior advisor to technology, data science, and business leaders
• Build strong relationships across global technology, data, risk, and compliance organizations
• Translate highly technical concepts into clear, actionable insights for non-technical stakeholders

Full Description

The Director of Data Analytics & Artificial Intelligence Audit will lead the design, execution, and evolution of audit coverage for advanced analytics, machine learning, artificial intelligence, and data governance across a global investment banking platform.

This role sits at the intersection of internal audit, technology risk, model risk management, and regulatory compliance, serving as a trusted advisor to senior management, regulators, and audit committees.

The successful candidate will bring a strong foundation in internal audit and risk management while demonstrating deep fluency in data architecture, analytics platforms, AI/ML models, and emerging technologies used across trading, risk, compliance, finance, and operations.

Key Responsibilities

Audit Strategy & Leadership

• Own and evolve the audit strategy for data analytics, artificial intelligence, machine learning, and advanced model usage across the enterprise

• Lead complex, global audits covering AI/ML models, automated decisioning, algorithmic processes, data pipelines, and analytics platforms

• Assess governance, controls, and risk management practices related to data quality, model lifecycle management, explainability, bias, and ethical AI

AI, Analytics & Model Risk Coverage

• Evaluate the design and effectiveness of controls across the full AI/ML lifecycle, including data sourcing, feature engineering, model development, validation, deployment, monitoring, and decommissioning

• Partner closely with Model Risk Management, Technology Risk, Cybersecurity, and Compliance teams to ensure aligned risk coverage

• Review usage of AI and analytics within front office, risk, finance, compliance, AML, operations, and corporate functions

Regulatory & Governance Oversight

• Assess compliance with global regulatory expectations related to model risk, data governance, privacy, and AI oversight

• Support regulatory examinations and inquiries related to analytics, models, and AI usage

• Present audit findings and risk themes to senior management, risk committees, and audit committees

Team Leadership & Capability Building

• Lead, mentor, and develop a team of audit professionals with analytics, technology, and quantitative skill sets

• Drive the use of data analytics and continuous auditing techniques within the Internal Audit function

• Influence the broader audit organization’s adoption of advanced analytics and AI-enabled audit methodologies

Stakeholder Engagement

• Serve as a senior advisor to technology, data science, and business leaders

• Build strong relationships across global technology, data, risk, and compliance organizations

• Translate highly technical concepts into clear, actionable insights for non-technical stakeholders

Required Qualifications

• 10+ years of experience in Internal Audit, or related roles within a large financial institution, consulting firm, or regulator

• Deep understanding of data analytics platforms, AI/ML models, and modern data architectures

• Strong knowledge of model risk management, governance frameworks, and control design

• Proven experience leading large, complex audits and managing senior-level stakeholders

• Ability to interpret regulatory guidance related to model risk, data governance, and emerging technologies

Preferred Qualifications

• Familiarity with cloud-based data platforms, big data technologies, and advanced analytics tools

• Background in quantitative disciplines, data science, computer science, or engineering

• Professional certifications such as CPA, CIA, CISA, FRM, or equivalent

What This Role Offers

• High-visibility leadership position within a global Internal Audit organization

• Direct exposure to senior management and regulators

• Opportunity to shape the firm’s approach to AI, analytics, and emerging technology risk

• Competitive compensation and long-term career growth within a global investment bank