Guardian
HeadofDataAnalytics,Automation,AI&ContinuousAuditing(DAACA)
“Head of Data Analytics, Automation, AI & Continuous Auditing (DAACA) at Guardian. Skills: Data Analytics, Automation, AI, Continuous Auditing. Define and execute DAACA vision, strategy, and roadmap. Position DAACA as a core pillar of audit”
What You'll Achieve.
Enhance audit quality, coverage, efficiency, and insight generation; Demonstrate measurable impact to Audit Leadership and the Audit & Risk Committee; Increase coverage; Reduce manual testing dependency; Improve consistency and scalability
Industry & Context.
Insight generation
3 days a week in office, 2 days a week WFH, Up to 10% travel
What They're Looking For.
Must Have
Bachelor's degree in a relevant field, 10+ years of experience, 5+ years implementing analytics, automation and/or AI within Internal Audit or Risk functions, Experience in AI/GenAI use cases and governance considerations, Proven ability to translate data/technology capabilities into business and audit value, Understanding of audit lifecycle, risk management, and control frameworks, Demonstrated people leadership and team development experience
Nice to Have
Experience with Python, SQL, Power BI/Tableau, Power Automate, Power Query, Alteryx, or similar tools, Experience with Copilot Studio and Claude Cowork, Experience in agile or product-based delivery models, Professional certifications (e.g., CIA, CISA, CPA, etc.), PhD preferred, Specific ML framework experience, Cloud platform certs
What You'll Do.
Define and execute DAACA vision
Position DAACA as a core pillar of audit
Advance continuous assurance and data-driven auditing
Identify and prioritize high-value use cases for analytics
Establish and track KPIs/KRIs
Drive value realization and ROI
Demonstrate measurable impact to Audit Leadership and the
Embed analytics and automation into end-to-end audit lifecycle
Expand continuous assurance
Shift from point-in-time reviews to ongoing risk coverage
Standardize reusable analytics and control libraries
Improve consistency and scalability
Partner with audit teams to increase coverage
Reduce manual testing dependency
Oversee development and delivery of scalable
Implement a product-oriented operating model
Ensure data engineering
and documentation standards
Evaluate and optimize tooling ecosystem
Balance transformative initiatives with ongoing delivery
Oversee development and delivery of scalable
Lead responsible adoption of AI/GenAI within Internal Audit
Identify and deploy AI use cases
Establish governance and controls framework(s) for AI usage
Ensure alignment with enterprise AI
Drive auditor upskilling on AI-enabled auditing techniques
Serve as primary interface between Internal Audit and
Influence adoption by acting as a trusted advisor
Partner with enterprise teams to leverage existing data
and stakeholder inquiries related to
Build and lead a high-performing multidisciplinary team
and training programs
Foster a culture of innovation
Develop a network of “DAACA Champions” embedded across
How You'll Work.
Team & Collaboration
Audit teams; Technology teams; Data teams; AI teams; Risk functions; Audit leadership; Business stakeholders; Enterprise teams
Communication Scope
Stakeholder inquiries; Trusted advisor
Process & Methodology
Product-oriented operating model, Agile, Product-based delivery models
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