Senior Director – Internal Audit Data Science and AI

Job description

Job Title:Senior Director Internal Audit - Data Science and AI

Locations: Reston VA or Washington DC or Open to Remote

Work Arrangements:

Hybrid Option: 3 or more days per week in office for candidates local to Washington DC or Reston VA

Remote Option:Must live in the 50 US states work Eastern Standard Time Zone Business hours (8:30-5 PM EST daily) and be willing to come into the DC or Reston VA office at least 1 time per quarter

Relocation Eligibility: Case-by-case

Compensation:Salary - USD $226000 $340000 / yr plus35% long term incentive cash bonus

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 Audits AI strategy analytics automation and enterprise technology delivery. 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.

Key Responsibilities

Lead the development and execution of Audits 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.

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.

Bachelors 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.