VP, Data, Analytics AI

Work Location

Chicago

Due to the highly interactive and team-based nature of this role, in-person attendance for most of the workweek (i.e., 3 days or more) is essential for: effective communication including during in-person meetings, strong supervision, real-time problem-solving, and participation in cross-functional initiatives.

Technology powers Ferrara’s transformation of iconic brands into a world-class global business. Following a successful S/4

HANA go‑live, our IT organization is leading the next phase of digital evolution—scaling platforms, advancing data and analytics, and partnering closely with the business to deliver measurable impact. This is a chance to join a highly innovative IT team with strong executive sponsorship and influence across the enterprise.

Reporting directly to the CIO, the VP, Data, Analytics & AI will partner with our business leaders in building our future. Our ambitious goals for expansion are driving us to transform our core business processes and build a technical landscape that improves the effectiveness of our company. Successful candidates will need to demonstrate prior leadership in driving positive change and having a seat at the table of the functional leadership team as well as the IT Leadership team.

Previous positions leading Analytics and Data will be considered an advantage.

The VP, Data, Analytics & AI is an executive 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 across the organization. This includes the creation and management of data and analytics strategy and operating model. The VP, Data, Analytics & AI is responsible for establishing, leading, and operating the data and analytics (D&A) function;

building trust and managing data; evolving technology capabilities; and developing talent and D&A culture.

• Strategy and Vision:
  Define the data, analytics, and AI strategy, including vision, drivers, and outcomes. Lead the creation and ensure the ongoing relevance of the organization’s D&A strategy in collaboration with the CEO, business domain leaders, CIO, and other relevant stakeholders.
• Operating Model:
  Institute an operating model for data, analytics, and AI that aligns with the capabilities and competencies required to execute the strategy. This includes the ecosystem, architectures, and delivery model.
• Partnerships:
  Build partnerships with executive leadership and board members to ensure data is managed as a business asset, AI-ready, and track and measure the value derived from those data assets. Communicate the tangible business value generated from data, analytics, and AI initiatives to stakeholders and executives.
• Data Governance:
  Maintain authority and accountability for data assets, analytics used for decision-making, and AI solutions that automate decisions and augment human performance. Oversee a centralized data management/data engineering service to ensure quality, traceability, timeliness, usability, and cost-effectiveness.
• Delivery Models:
  Oversee delivery models, methods, and practices for creating data, analytics, and AI products to ensure consistent application and use of data and analytics solutions and services, including data science.
• Technology Capabilities:
  Evolve technology capabilities for the D&A platform in collaboration with the CIO to align D&A initiatives with IT infrastructure and policies and drive technology innovation across the organization.
• Governance Mechanisms:
  Establish and maintain trust in AI-ready data assets by instituting governance mechanisms for data, including fostering data stewardship across business data domains. Collaborate with leaders responsible for security, privacy, risk, and compliance.
• Regulatory Compliance:
  Understand regulatory requirements, relevant data protection laws and regulations, and industry-specific standards. Ensure the organization's data practices are compliant in collaboration with legal and compliance teams.
• Ethical Use of Data:
  Oversee the ethical and responsible use…