Executive Director – Head of Finance Transformation, Data & AI

Lead the strategy and multi-year roadmap to modernize FP&A through data analytics automation and AI - delivering measurable improvements in productivity cycle time reporting quality and decision support. Partner closely with the Finance community to drive change management and adoption. You will shape key design decisions own the product roadmap and oversee delivery of new capabilities across the organization.

Responsibilities

Transformation Strategy

• Define and execute a multi-year FP&A Transformation and AI strategy aligned to Finance and business objectives.
• Set near-term initiatives and long-term investments across data analytics automation AI reporting and workflow optimization.
• Establish value-realization metrics (e.g. productivity cycle-time reduction reporting quality decision support).

Data & Analytics Leadership

• Define Finance data strategy and target-state architecture.
• Improve data quality governance lineage and accessibility across Finance datasets.
• Build scalable data models and semantic layers for reporting forecasting and management information.
• Partner withCIB Financial Analysisto create trusted reusable Finance data assets.
• Expand modern analytics capabilities and self-service reporting adoption.

AI & Automation Enablement

• Identify and prioritize high-value GenAI agentic AI and intelligent automation use cases across FP&A.
• Establish frameworks for safe controlled and compliant AI use within Finance.
• Drive adoption of AI productivity tools (e.g. Microsoft Copilot and otherapprovedLLM platforms).
• Automate recurring reporting commentary generation variance analysis forecasting support and MI production.
• Track emerging AI capabilities and maintain a forward-looking adoption roadmap.

Solution Delivery

• Lead a team of developers data engineers and automation specialists.
• Implement agile delivery practices and governance; oversee end-to-end design build and deployment.
• Ensure solutions meet enterprise requirements for security controls compliance and resilience.
• Serve as senior technical advisor to Finance leadership.

Change Management & Capability Building

• Build an AI-enabled culture across FP&A.
• Create and lead a Finance AI Academy and upskilling program.
• Develop training communities of practice and adoption programs with measurable outcomes.

Stakeholder Management

• Partner with senior Finance leaders CFO organizations and global Technology/Data teams.
• Influence critical design decisions and secure alignment on priorities and investment.

Required Experience

• 12 years across Finance Transformation Data/Analytics AI/Automation or Technology leadership.
• Proven delivery of large-scale transformation in Financial Services / Banking / Capital Markets.
• Experience building and leading multi-disciplinary teams and delivering measurable business outcomes.
• Strong executive communication and stakeholder influence.

Technical Skills

Data & Analytics:Python SQL data modeling/architecture data governance & quality frameworks cloud data platforms (e.g. Snowflake/Databricks/Azure) BI/visualization (Power BI/Tableau).

AI & ML:GenAI solution design LLMs prompt/workflow design RAG agentic AI frameworks AI governance/risk/controls model evaluation/monitoring.

Platforms & Tools:Microsoft Copilot OpenAI/ChatGPT Enterprise Anthropic Claude GitHub Copilot Azure AI Services LangChain/LangGraph/LlamaIndex vector databases/knowledge platforms.

Automation & Engineering:API integration workflow orchestration Power Automate UiPath process mining CI/CD & DevOps fundamentals SDLC management.

Success Measures (First 12 Months)

• Publish and execute a Finance AI & Transformation roadmap.
• Deliver measurable productivity gains across FP&A processes and reduce manual reporting effort through automation.
• Improve Finance data quality and accessibility; increase adoption of AI-enabled tools.
• Establish a sustainable AI/analytics capability (operating model training and adoption) that improves decision support and management information quality.