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VP, Finance - Business Intelligence & AI Adoption

March 6, 2026

About the position

Equifax is where you can power your possible. If you want to achieve your true potential, chart new paths, develop new skills, collaborate with bright minds, and make a meaningful impact, we want to hear from you. 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.

Responsibilities

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 transparency 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.

Requirements

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).

Nice-to-haves

MBA or Master's degree in a quantitative discipline is highly desirable.

Benefits

comprehensive compensation and healthcare packages
401k matching
paid time off
organizational growth potential through our online learning platform with guided career tracks

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Common Interview Questions And Answers

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