Vice President - VP Analytics and Artificial Intelligence; AI Data

Overview

The Vice President (VP) Analytics and AI Data is an executive business leadership role focused on leveraging data, analytics, and AI to drive business value, foster a data-driven culture, and ensure the effective governance and utilization of data assets and ecosystem across the organization. This role is responsible for the creation and management of the data and analytics strategy and operating model.

The VP Analytics and AI Data is responsible for establishing, leading, and operating the data & analytics (D&A) function; building trust and managing data; evolving technology capabilities; and developing talent and D&A culture. The incumbent will have a broad understanding of the full range of strategic data and analytics capabilities and the ability to communicate these concepts, methods, and techniques in ways easily understood by other stakeholders.

This VP is also responsible for supporting organizational AI initiatives and understanding AI concepts and applications and AI's applicability within the enterprise. The incumbent understands business objectives and goals; maintains industry domain expertise; and utilizes knowledge of D&A concepts, methods, and techniques, demonstrating the ability to engage and communicate with key stakeholders at all levels of the organization. The VP will facilitate AI and data-driven vision, strategy, and operating models.

Responsibilities listed in this section are core to the position. Inability to perform these responsibilities, with or without an accommodation, may result in disqualification from the position.

• Defines data, analytics, and AI strategy, including vision, drivers, and outcomes. Leads the creation (and assures the ongoing relevance) of the organization's D&A strategy in collaboration with the CEO, business domain leaders, CIO, and other relevant stakeholders.

• Institutes an operating model for data, analytics, and AI that is consistent with the capabilities and competencies required to execute the strategy. The operating model includes the ecosystem, architecture, and delivery model.

• Builds partnerships with executive leadership and board members to ensure that data is being managed as a business asset, data is AI-ready, and by tracking and measuring the value derived from those data assets. Communicates the tangible business value generated from data, analytics, and AI initiatives to stakeholders and executives.

• Maintains authority and accountability for the data assets, analytics used for decision making, and AI solutions that automate decisions and augment human performance. Creates and oversees a centralized data management/data engineering service for sharing certified data products to ensure quality, traceability, timeliness, usability, and cost-effectiveness.

• Oversees delivery models, methods, and practices for creation of data, analytics, and AI products and to ensure consistent application and use of data and analytics solutions and services, including data science.

• Evolves technology capabilities for the D&A platform, in collaboration with the Chief Information Officer (CIO), to align D&A initiatives with IT infrastructure and policies and drive technology innovation across the organization.

• Establishes and maintains trust in AI-ready data assets by instituting governance mechanisms for data including fostering data stewardship across business data domains. Includes other leaders that share responsibility for data, such as security, privacy, risk, and compliance leaders.

• Understands regulatory requirements, relevant data protection laws and regulations, such as GDPR, EU AI Act, and CCPA, and industry-specific standards. Ensures the organization's data practices are compliant, in collaboration with legal and compliance.

• Oversees the ethical and responsible use of data and algorithms used for artificial intelligence, analytics, and automated decision making. Establishes guidelines and practices that prevent misuse of data and protect individual privacy beyond regulatory and compliance requirements.

• Owns the development of a data-driven culture and related competencies, behaviors, and data and AI literacy across the enterprise. Leads transformation efforts by developing D&A talent and maturing the D&A capability of the organization.

• Leads data-driven innovation for the enterprise, including investigation, adoption, and exploitation of artificial intelligence. Identifying new kinds, types, and sources of data to enable business value innovation throughout the organization and enable new use cases. Monitors for emerging skills and technologies, focusing on accelerating business innovation and transformation.

• Provides AI-ready data, supporting graph analysis, prompt engineering, machine learning, and natural language processing.

• Leads research, strategy creation, and development of new AI and data and analytics products or services to support marketing activities and impact enterprise profitability.

• Drives and oversees major…