Senior Director - Audit AI, Product & Data Science

Job Description

Job Description

JOB SUMMARY: In this dynamic senior leadership position in Audit, you will lead the AI, Product, and Data Science vision and be responsible for advancing Audit's AI strategy, analytics, automation, and enterprise technology delivery. You will build and scale industry-leading technology solutions that improve audit and overall enterprise risk management quality, efficiency, and insight generation while maintaining a well-managed governance of analytics and technology enablers. Your team will partner across Audit, Technology, Enterprise AI, data science, and risk organizations to architect reusable products in a unified platform to deliver AI-enabled capabilities that strengthen risk detection, continuous monitoring, evidence generation, and control-risk reporting. You will be accountable to build a team with high-performing top talent, delivering measurable efficiency and insight-gains, and positioning Audit as a beacon for innovation across the enterprise.
LOCATION & WORK ARRANGEMENT:

• Local Candidates (Washington, DC / Reston, VA area): This is a hybrid role requiring 3 or more days per week in the office.
• Remote Candidates (Outside the DC area): Remote employment is available under the following conditions:
  1. Must reside within any of the 50 US states .
  2. Must work Eastern Standard Time (EST) business hours (8:30 AM 5:00 PM EST daily).
  3. Must be willing to travel to the Washington, DC or Reston, VA office at least 1 time per quarter (with potential for more frequent visits based on business needs).

THE IMPACT YOU WILL MAKE: The Senior Director - Audit AI, Product and Data Science role will offer you the flexibility to make each day your own while working alongside people who care so that you can deliver on the following responsibilities:

• Lead the development and execution of Audit's AI, analytics, and automation roadmap in alignment 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 produce measurable efficiency, quality, and insight gains across the audit lifecycle.
• Partner with Technology to architect and scale a unified audit platform that enables reusable data assets, analytics, automation, GenAI services, model operations, secure delivery, and enterprise-grade controls.
• Build destination talent by attracting, developing, and retaining high-performing data science, AI engineering, product, and automation professionals while upskilling the existing audit workforce.
• Serve as a strategic thought leader to Audit executives and VP stakeholders, challenging the organization to maximize value from 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 allows auditors to focus on work requiring professional judgment while AI supports 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, more robust risk detection, automated evidence generation, and deeper data-driven insights that establish Audit as a beacon of innovation and a destination for technical and future-skilled audit talent.

THE EXPERIENCE YOU BRING TO THE TEAM:
Minimum Required Experiences:

• 8 years of relevant experience in data science, AI, analytics, automation, product management, technology delivery, audit technology, or related enterprise technology functions.
• 5 years of leadership experience building, coaching, and leading high-performing, diverse teams of data science, AI, automation, product, and technology professionals.
• Proven track record 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/product delivery practices.
• Experience partnering with Technology to design and scale platforms, reusable capabilities / microservices, governed data products, APIs, and enterprise-grade AI capabilities.
• 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, with the ability to advise executives and VP stakeholders, challenge assumptions, and explain technical ideas 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.
• Bachelor's degree or equivalent experience in computer science, data science, statistics, engineering, information systems, business or a related field.
• Shows curiosity and adaptability in learning and responsibly applying new technologies, including artificial intelligence, to reimagine how we work.

Desired Experiences:

• Advanced degree in computer science, data science, statistics, engineering, AI, analytics, business, finance, audit, risk, or a related field.
• Strong understanding of Audit, controls or risk management.
• Experience with GenAI/LLMs, retrieval-augmented generation, intelligent agents, NLP, anomaly detection, machine learning, orchestrated multi-agentic 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 / AI certifications, or equivalent professional experience.