SVP, Chief Data & Analytics Officer

Description

The Chief Data & Analytics Officer (CDAO) is the enterprise executive responsible for maximizing business value from data, analytics, automation, and artificial intelligence. Serving as a key member of the senior leadership team, the CDAO partners across Business Lines, Operations, Customer Service, Credit, Fraud, Marketing, Risk, Finance, Technology, Human Resources, and Corporate Functions to accelerate strategic priorities, improve decision quality, enhance productivity, and create sustainable competitive advantage. The CDAO is both a functional leader and an enterprise transformation executive. While directly leading teams responsible for data governance, analytics, AI strategy, data products, business intelligence, and decision science, the primary mission of the role is enabling the broader organization to achieve superior business outcomes through the effective application of data, analytics, automation, and artificial intelligence.

Key Responsibilities

• Serve as a strategic advisor to the Executive Committee, and business leaders on opportunities to accelerate growth, improve customer outcomes, reduce risk, and increase productivity through data, analytics, automation, and AI.
• Partner across Business Lines, Operations, Customer Service, Credit, Fraud, Marketing, Finance, Risk, and Corporate Functions to identify, prioritize, and execute high-value transformation initiatives.
• Help shape enterprise strategy through data-driven insights, predictive analytics, and AI-enabled opportunities.
• Drive measurable business outcomes including revenue growth, credit performance, fraud mitigation, customer satisfaction, productivity improvement, operating leverage, shareholder value creation, and risk management.
• Establish a culture of fact-based decision making and enterprise accountability for results.
• Further define and execute the enterprise AI vision and multi-year roadmap aligned to corporate strategy and business objectives.
• Lead the company’s transformation toward becoming an AI-First financial institution, embedding AI into customer experiences, employee workflows, operational processes, risk management, servicing, and decision-making capabilities.
• Establish and govern the enterprise AI portfolio, ensuring investments and execution are aligned to strategic priorities and measurable business outcomes.
• Drive enterprise adoption of generative AI, machine learning, intelligent automation, and emerging technologies across business and staff organizations.
• Partner with executive leaders to redesign work, operating models, customer journeys, and business processes to fully leverage AI-enabled capabilities.
• Lead enterprise change management efforts necessary to accelerate AI adoption and realization of business benefits.
• Develop and execute the enterprise AI talent strategy, including workforce readiness, capability development, recruiting, training, and AI literacy across the organization.
• Serve as the executive sponsor and champion for enterprise AI transformation.
• Establish measurement frameworks to track AI adoption, productivity gains, financial impact, customer outcomes, employee effectiveness, and risk performance.

Data, Analytics & Governance

• Establish and execute a comprehensive enterprise data and analytics strategy aligned to business objectives and regulatory expectations.
• Lead enterprise data governance, data quality, metadata management, lineage, stewardship, and critical data element management.
• Ensure the availability of trusted, governed, and actionable data across the enterprise.
• Lead advanced analytics, decision science, business intelligence, and data product capabilities that support strategic and operational decision making.
• Establish enterprise standards for reporting, analytics, data quality, and information management.
• Promote consistent and scalable use of data assets across the organization.

Risk, Compliance & Responsible AI

• Establish governance and control frameworks supporting responsible, transparent, and compliant use of data and AI.
• Partner with Risk, Compliance, Legal, Information Security, Fair Lending, Privacy, and Model Risk Management to ensure adherence to internal policies and regulatory expectations.
• Ensure appropriate oversight of AI, machine learning, and advanced analytics solutions, including model governance, explainability, monitoring, and risk management.
• While ensuring risk is effectively managed – drive a highly efficient enabling environment.
• Support regulatory, audit, and governance activities related to data, analytics, and AI.

Talent & Organizational Leadership

• Build and lead a high-performing organization spanning data governance, analytics, business intelligence, data science, AI, data products, and decision science.
• Attract, develop, and retain top talent in data, analytics, AI, and related disciplines.
• Foster a culture of innovation, experimentation, continuous learning, and business partnership.
• Improve enterprise data literacy and AI fluency across all levels of the organization.

Required Qualifications

• 15+ years of progressive leadership experience in data, analytics, artificial intelligence, decision science, or related disciplines.
• Significant executive leadership experience within financial services, banking, payments, credit cards, fintech, or other highly regulated industries.
• Demonstrated success leading enterprise-scale transformation initiatives that produced measurable business outcomes.
• Deep expertise in analytics, AI, data governance, business intelligence, decision science, and modern data management practices.
• Strong understanding of consumer financial services, including credit, fraud, marketing, servicing, operations, risk, and customer experience.
• Proven ability to influence executive stakeholders and lead cross-functional transformation efforts.
• Excellent communication skills, strong partner to the business and staff areas.
• Proven ability to build and lead high-performing teams and organizational capabilities.

Preferred Qualifications

• Prior Chief Data Officer, Chief Analytics Officer, Chief Data & Analytics Officer, or equivalent enterprise leadership experience.
• Experience leading large-scale AI transformation initiatives within financial services.
• Experience modernizing enterprise data ecosystems and enabling cloud-based analytics and AI capabilities.
• Strong understanding of emerging AI technologies, generative AI, intelligent automation, and enterprise adoption strategies.
• Advanced degree in Business, Statistics, Economics, Computer Science, Engineering, Data Science, Applied Mathematics, or a related field.