Senior Director – Internal Audit - Data Science and AI
Posted Updated
Summary
Onsite Senior Director role in Reston, VA leading Internal Audit's AI, data science, and automation strategy at a financial-services enterprise. The person builds a unified audit platform with GenAI, analytics, and continuous-monitoring capabilities while leading a small team and staying hands-on with model development and coding. Salary $226k-$340k plus 35% bonus.
POSITION: Senior Director – Internal Audit - Data Science and AI
LOCATION: Reston, VA
WORK TYPE: Onsite
SALARY: $226,000 - $340,000/yr (plus 35% long-term incentive cash bonus)
TYPE: Permanent
CATEGORY: Accounting / Finance JOB DESCRIPTION: 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 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. THE IMPACT YOU WILL MAKE In this role, you will 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.
• Demonstrates 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. NOTE: This is a hands-on technical leadership role. The ideal candidate will actively contribute to AI model development and coding work while leading a small, highly technical team, rather than moving away from hands-on technical responsibilities. ---
SCREENING QUESTIONS:
1. Walk us through a specific example where you personally developed or contributed to an AI/ML model or analytics solution while simultaneously leading a technical team. How did you balance hands-on technical work with your leadership responsibilities?
2. Describe your experience designing and scaling enterprise platforms with reusable data assets, APIs, and microservices. What governance and controls did you implement for data products and AI capabilities?
3. Tell us about a time you led an AI-enabled transformation initiative in Internal Audit, risk, compliance, or a highly regulated financial services environment. What were the measurable business outcomes and efficiency gains?
4. Can you discuss your hands-on expertise with AI/ML, GenAI, and advanced analytics? What specific technical work have you personally performed in the past two years beyond supervision and strategy?
5. How have you approached responsible AI, model risk management, and regulatory compliance in your previous roles? Describe the specific governance frameworks you established.
6. Walk us through your experience building and coaching high-performing data science and AI engineering teams. How do you maintain credibility and influence as a hands-on technical contributor and strategic thought leader with executives?
7. Describe your experience with cloud AI platforms, MLOps/LLMOps, and model lifecycle management. What cloud technologies and DevOps practices have you directly worked with?
LOCATION: Reston, VA
WORK TYPE: Onsite
SALARY: $226,000 - $340,000/yr (plus 35% long-term incentive cash bonus)
TYPE: Permanent
CATEGORY: Accounting / Finance JOB DESCRIPTION: 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 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. THE IMPACT YOU WILL MAKE In this role, you will 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.
• Demonstrates 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. NOTE: This is a hands-on technical leadership role. The ideal candidate will actively contribute to AI model development and coding work while leading a small, highly technical team, rather than moving away from hands-on technical responsibilities. ---
SCREENING QUESTIONS:
1. Walk us through a specific example where you personally developed or contributed to an AI/ML model or analytics solution while simultaneously leading a technical team. How did you balance hands-on technical work with your leadership responsibilities?
2. Describe your experience designing and scaling enterprise platforms with reusable data assets, APIs, and microservices. What governance and controls did you implement for data products and AI capabilities?
3. Tell us about a time you led an AI-enabled transformation initiative in Internal Audit, risk, compliance, or a highly regulated financial services environment. What were the measurable business outcomes and efficiency gains?
4. Can you discuss your hands-on expertise with AI/ML, GenAI, and advanced analytics? What specific technical work have you personally performed in the past two years beyond supervision and strategy?
5. How have you approached responsible AI, model risk management, and regulatory compliance in your previous roles? Describe the specific governance frameworks you established.
6. Walk us through your experience building and coaching high-performing data science and AI engineering teams. How do you maintain credibility and influence as a hands-on technical contributor and strategic thought leader with executives?
7. Describe your experience with cloud AI platforms, MLOps/LLMOps, and model lifecycle management. What cloud technologies and DevOps practices have you directly worked with?