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Senior Data Leader for AI

hace 2 meses

Madrid Centro, Madrid, España Ferrovial Agroman A tiempo completo

About Us: Ferrovial Agroman is a leading infrastructure operator, committed to developing sustainable solutions. Our company operates in over 15 countries and has a workforce of over 24,000 professionals worldwide. Ferrovial Agroman is listed on multiple stock markets and is a member of the Dow Jones Sustainability Index and FTSE4Good. Our aim is to design the Company's strategy, establishing global policies, guidelines, and action guides related to the different functional areas of the Organization.

Job Description: At Ferrovial Agroman, we believe in leveraging Artificial Intelligence (AI) as a key driver for creating business value. AI has the power to transform our operations and enhance decision-making, but its true potential can only be realized with high-quality data. Data is the lifeblood of AI, fueling its ability to deliver innovative solutions and insights. To achieve this, we are looking for a senior professional with proven experience in managing data in the context of AI Programs.

Key Responsibilities:

  1. Strategy Development:
    • Align with the AI Program Manager to understand business AI-Driven use cases.
    • Prioritize data needs according to the potential business value and data feasibility.
    • Coordinate data needs among different stakeholders and data teams.
    • Act as a facilitator for the AI Program.
    • Participate in the AI Program Governance committee to report data activities issues.
  2. Use Case Delivery:
    • Identify relevant data sources (internal or external).
    • Identify relevant data owners and stewards across the organization.
    • Facilitate sample data (structured or non-structured) to start with an AI use case (MVP).
    • Grant data protection and privacy policies in AI use cases.
    • Identify data quality issues and coordinate teams to promote remediation plans.
    • Promote the use of standards and best practices designed by Ferrovial Agroman.
    • Propose data platforms evolution, if needed to manage AI use cases more effectively.
    • Stay up-to-date with market trends, being proactive in testing and adoption, if suitable.
    • Promote the evolution of data platforms, data policies, or data & AI governance rules.
  3. Roll Out:
    • Participate in the industrialization phase.
    • Define data needs for each use case (resources and budget).
    • Coordinate different stakeholders and system integrators to automate data access.
    • Coordinate different data teams to evolve their data platform, if needed.
    • Measure the data value contribution to each use case.

Requirements:

  • Strategic mindset to analyze each use case business value.
  • At least 5 years of experience leading data teams in a context of AI use cases.
  • At least 1 year being involved in Gen AI Use cases.