What are the responsibilities and job description for the VP, Finance - Business Intelligence & AI Adoption position at Equifax?
VP of Finance - Business Intelligence & AI Adoption
This is a senior leadership position responsible for defining and executing the strategy for business intelligence (BI), financial planning and analysis (FP&A) technology, and the aggressive adoption and deployment of Artificial Intelligence (AI) and Machine Learning (ML) capabilities to transform FP&A reporting and insights. The VP will focus on leveraging AI to centralize, standardize, and elevate the quality of financial reporting, driving a data-driven culture and enhancing the predictive accuracy of FP&A models.
Key Responsibilities
Strategy and Leadership
This is a senior leadership position responsible for defining and executing the strategy for business intelligence (BI), financial planning and analysis (FP&A) technology, and the aggressive adoption and deployment of Artificial Intelligence (AI) and Machine Learning (ML) capabilities to transform FP&A reporting and insights. The VP will focus on leveraging AI to centralize, standardize, and elevate the quality of financial reporting, driving a data-driven culture and enhancing the predictive accuracy of FP&A models.
Key Responsibilities
Strategy and Leadership
- Develop and Champion AI FP&A Reporting Strategy: Define the vision, roadmap, and organizational change management required to successfully adopt and deploy AI/ML within the FP&A.
- BI and Data Governance: Oversee the enterprise-wide financial BI platforms, ensuring data accuracy, integrity, and robust governance frameworks.
- Team Leadership: Lead, mentor, and grow a high-performing team of BI specialists,, financial analysts, and technology professionals, fostering a culture of innovation and continuous improvement.
- Cross-Functional Partnership: Collaborate closely with the Business Unit Finance & Accounting teams, including the BI focals, Financial Systems Leader, IT, FP&A, Accounting, and other business unit leaders to prioritize initiatives and ensure alignment of BI and AI/ML deployments with overall corporate strategy.
- AI Governance and Compliance: Design and implement a robust AI governance framework, establishing clear policies, ethical guidelines, and risk management protocols to ensure the compliant, responsible, and non-biased use of AI/ML models across the Finance organization, with specific auditability standards for FP&A forecasting and budgeting models.
- AI/ML and Advanced Analytics Deployment and Integration : Lead the selection, proof-of-concept, and enterprise-wide deployment of AI/ML tools and platforms relevant to Finance operations, ensuring seamless integration with existing ERP and financial systems.
- Predictive Modeling: Drive the development and use of advanced predictive and prescriptive models for critical financial processes, including forecasting, budgeting, risk management, and capital allocation, while establishing model governance and auditability standards to ensure tr ansparency and trust in all FP&A outputs .
- Process Automation: Identify and implement opportunities for leveraging Robotic Process Automation (RPA) and AI to automate repetitive, high-volume financial tasks, freeing up the Finance team for strategic work.
- AI Powered Reporting and Standardization: Lead the strategic use of AI to transform existing financial reporting into dynamic, interactive BI dashboards. Establish the centralized model and governance to guide, and certify AI-powered reporting standards across all FP&A outputs , ensuring accuracy and consistency for executive and operational insights. And operational teams.
- Data Translation: Act as the key interpreter between technical teams and non-technical finance and business stakeholders, ensuring AI outputs and data insights are actionable and well-understood.
- Strategic Vision: Ability to conceptualize and articulate a long-term strategic vision for technology and data that aligns with business goals.
- Change Management: Proven ability to lead organizational change and drive the adoption of new, sometimes disruptive, technologies.
- Communication: Exceptional written and verbal communication skills, with the ability to present complex technical and financial information to executive and board-level audiences.
- Results-Oriented: A strong track record of delivering measurable business results through data and technology initiatives.
- Bachelor's degree in Finance, Accounting, Data Science, Computer Science, or a related quantitative field.
- 12 years of progressive experience in Finance, Business Intelligence, or Financial Technology, with at least 5 years in a senior leadership role focused on advanced analytics, data science, or AI/ML deployment.
- Proven, hands-on experience leading the design, implementation, and successful adoption of AI/ML solutions in a corporate or financial environment.
- Deep understanding of core financial processes, including FP&A, budgeting, forecasting, and month-end close.
- Expert knowledge of BI tools (e.g., Tableau,, Looker, Oracle OTBI), data warehousing (e.g, Google Cloud Big Query, and experience with data science platforms and programming languages (e.g., Python, R).
- MBA or Master's degree in a quantitative discipline is highly desirable.