Senior Data Leader For Ai

hace 3 meses


Madrid, España Ferrovial Agroman Sa A tiempo completo

.About us:Ferrovial is one of the world's leading infrastructure operators, committed to developing sustainable solutions.Our company operates in more than 15 countries and has a workforce of over 24,000 professionals worldwide. Ferrovial is listed simultaneously on 3 stock markets: USA (Nasdaq), the Netherlands (Euronext Amsterdam), and Spain (IBEX 35), and is a member of the Dow Jones Sustainability Index and FTSE4Good.The aim of Ferrovial Corporation is to design the Company's strategy, establishing global policies, guidelines and action guides related to the different functional areas of the Organization (Internal Audit, Finance, Human Resources, Legal, IT, Innovation, etc.), which subsequently are developed and adapted to the specificities of each Business Unit. Additionally, it performs a function of providing corporate services to the different companies of the group, while consolidating its information.Job Description:At our company, 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 it, we are looking for a senior professional with proven experience in managing data in the context of AI Programs.Is that you? Then, keep readingFunctions:Reporting to the Global CDO (Spain based) you will:Strategy:Be fully aligned 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.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.Propose data platforms evolution, if needed to manage AI use cases more effectively.Be up to date with market trends, being proactive in the test and adoption, if suitable.Promote the evolution of data platforms, data policies or data & AI governance rules.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


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