AVP, Finance Data & AI

The AVP, Finance AI & Data – Strategy & Enablement role is a leadership opportunity to shape the future of how Finance leverages data and AI to transform FP&A, reporting, and operations. This role directly contributes to the mission by building Finance’s AI strategy, driving responsible adoption, strengthening data governance, and enabling secure, scalable solutions that align with enterprise standards. The leader will play a pivotal role in accelerating AI use cases, uplifting AI literacy, and creating a strong data foundation across Finance, partnering closely with technology, analytics, architecture, and risk teams. In return, they gain the opportunity to shape enterprise‑level transformation, influence senior stakeholders, build communities of practice, and lead innovative programs that materially improve business outcomes. This role offers a unique chance to drive strategy while also seeing tangible impact through execution.

Position Responsibilities:

• Shape and lead the multi‑year AI strategy for Finance, identifying high‑value AI and analytics use cases and maintaining a prioritized roadmap aligned to Finance’s transformation goals.
• Oversee design, deployment, and performance of AI solutions, ensuring responsible use, strong governance, and measurable business outcomes across Finance workflows and platforms.
• Drive AI literacy and citizen development, building training programs, guardrails, and a Finance AI Community of Practice to accelerate adoption and innovation.
• Lead Finance’s data strategy, governance, and enablement, ensuring high‑quality, well‑governed, accessible data; supporting GDO policies; and advancing curated data layers and semantic models.
• Partner across Finance, IT, enterprise data, and risk teams to implement governance tools, align with global standards, and ensure secure, scalable, compliant data and AI solutions.
• Guide data delivery teams and Finance consumers on optimal data usage, documentation, and best practices across platforms such as Power BI, Alteryx, and Anaplan​

Must-Have Skills and Experience

• Extensive Finance & Transformation Experience: A strong finance background with roughly 8–10+ years of experience in finance or financial services, including roles in finance transformation, analytics, or strategy. The ideal candidate has a deep understanding of core finance processes (planning, forecasting, accounting, reporting) and how they interconnect, enabling them to identify where data and AI can make an impact. Leadership exposure in large-scale projects or change programs is essential.

• Experience leading end-to-end implementation of technology or data projects in Finance.
• Extensive working experience with accounting, finance and IT professionals, with ability of understanding complex AI and Data concepts
• Data Management & Governance Expertise: In-depth knowledge of data governance principles (data lineage, metadata management, data stewardship) and hands-on experience with tools/technologies for data integration and business intelligence are required.
• Understanding of finance data (FP&A, accounting, reporting) processes.
• Familiarity with tools such as Alteryx, Power BI, Power Apps, SQL Server, and metadata documentation practices.
• Experience guiding data delivery teams and consumers in optimal data usage (e.g. EDL layers, Power BI, Alteryx, Anaplan).
• General understanding/ awareness in data governance, including data classification, security, retention, access control, and monitoring.
• AI and Analytics Acumen: Strong working knowledge of AI/analytics technologies and their applications in business. The candidate does not need to be a data scientist, but should understand concepts like machine learning, predictive modeling, process automation, and AI governance. They should be familiar with common AI use cases in finance and emerging trends (for example, predictive forecasting, AI in risk assessment, NLP for report generation).
• Strategic Thinker with Execution Ability: Visionary planning skills to set a forward-looking strategy, combined with the practical ability to execute complex programs. The AVP must be adept at formulating a clear strategy and actionable roadmap, then driving it to completion through measurable milestones. This requires strong project/program management skills, the ability to prioritize initiatives, and comfort managing ambiguity and evolving priorities. They should have a results-driven mindset, ensuring that data/AI initiatives tangibly improve business outcomes.
• Exceptional Stakeholder Management and Communication: Excellent communication skills are mandatory – both in articulating complex ideas in simple terms and in active listen