Senior Director, Internal Audit - Data Science and AI

Job Type: Permanent

Location: Reston, VA; Washington, DC; or remote. Relocation assistance: Available, subject to eligibility and business need. Remote work may also be available.

In this senior leadership position, you will lead the AI, product, and data science vision for Audit and advance Audit’s AI strategy, analytics, automation, and enterprise technology delivery. You will build and scale technology solutions that improve audit and enterprise risk management quality, efficiency, and insight generation, while ensuring effective governance of analytics and technology. You will partner across Audit, Technology, Enterprise AI, data science, and risk organizations to develop reusable products on a unified platform. These products will deliver AI-enabled capabilities that strengthen risk detection, continuous monitoring, evidence generation, and control-risk reporting. You will build a high-performing team, deliver measurable efficiency and insight gains, and position Audit as an innovator across the enterprise.

The Impact You Will Make

This role offers the flexibility to shape your work while collaborating with colleagues to:

• Lead the development and execution of Audit’s AI, analytics, and automation roadmap, aligned with Board goals, Audit priorities, and the broader enterprise AI vision.
• Own the strategy, product roadmap, delivery, and adoption of AI, GenAI, analytics, and automation capabilities that deliver measurable efficiency, quality, and insight gains across the audit lifecycle.
• Partner with Technology to architect and scale a unified audit platform that supports reusable data assets, analytics, automation, GenAI services, model operations, secure delivery, and enterprise-grade controls.
• Attract, develop, and retain high-performing data science, AI engineering, product, and automation professionals, while upskilling the existing audit workforce.
• Advise Audit executives and VP+ stakeholders, championing the value of AI and advanced analytics while managing data, model, operational, and ethical risks.
• Shape a platform-based approach that reduces time to market, increases reuse, and enables auditors to focus on work requiring professional judgment, with AI supporting anomaly detection, full-population testing, evidence generation, actionable insights, and control-risk reporting.
• Collaborate with Enterprise AI, data science, technology, risk, compliance, and business leaders to extend Audit-built capabilities across the three lines of defense and improve enterprise risk management effectiveness.
• Enable continuous monitoring, stronger risk detection, automated evidence generation, and deeper data-driven insights, while supporting Audit’s innovation and attracting technical and future-skilled audit talent.

The Experience You Bring to the Team

Minimum Required Experience

• At least 8 years of relevant experience in data science, AI, analytics, automation, product management, technology delivery, audit technology, or related enterprise technology functions.
• At least 5 years of leadership experience building, coaching, and leading high-performing, diverse teams of data science, AI, automation, product, and technology professionals.
• A proven track record of delivering enterprise AI, analytics, automation, or data products from strategy through production adoption, with measurable business outcomes.
• Experience leading AI-enabled transformation in Internal Audit, risk, compliance, financial services, or another highly regulated enterprise environment.
• Deep expertise in AI/ML, GenAI, automation, advanced analytics, data platforms, cloud technologies, model lifecycle management, and scalable software or product delivery practices.
• Experience partnering with Technology to design and scale platforms, reusable capabilities or microservices, governed data products, APIs, and enterprise-grade AI capabilities.
• A strong understanding of data governance, model risk, responsible AI, and regulatory expectations in financial services or similarly regulated environments.
• Executive-level communication and influencing skills, including the ability to advise executives and VP+ stakeholders, challenge assumptions, and explain technical concepts clearly to non-technical audiences.
• Experience establishing strategies, operating models, talent plans, and performance measures that accelerate delivery, reuse, workforce adoption, and measurable efficiency gains.
• A bachelor’s degree or equivalent experience in computer science, data science, statistics, engineering, information systems, business, or a related field.
• Curiosity and adaptability in learning and responsibly applying new technologies, including artificial intelligence, to reimagine how we work.

Desired Experience

• An advanced degree in computer science, data science, statistics, engineering, AI, analytics, business, finance, audit, risk, or a related field.
• A strong understanding of audit, controls, or risk management.
• Experience with GenAI/LLMs, retrieval-augmented generation, intelligent agents, NLP, anomaly detection, machine learning, orchestrated multi-agent workflows, or knowledge graphs.
• Familiarity with cloud AI and data platforms, MLOps/LLMOps, model monitoring, data quality controls, secure software delivery, and enterprise architecture practices.
• Relevant certifications or credentials, such as machine learning, cloud, or AI certifications, or equivalent professional experience.