Where Innovation Meets Opportunity Are you ready to elevate your career with a global leader in infrastructure solving complex problems and generating a positive outcome on people’s lives? At Ferrovial , we are not just a company; Ferrovial is also leading the development of the New Terminal One at JFK International Airport. Nasdaq100 Index) and the Spanish Stock Exchanges (IBEX 35). Ferrovial is included in globally recognized sustainability indices such as the Dow Jones Best-in-Class Index. Ferrovial’s activity is carried out through our business units, including Highways, Airports, Construction, and Energy. Our Corporate organization oversees business activities, providing strategic planning, communication, legal, finance and human resources services to the business units. As a member of our corporate organization, you will have a broad view of our company, further supporting your career development. General presence, local impact : Be part of a company that is shaping the future of infrastructure worldwide, with challenging roles and projects that make a real difference. Thrive in an innovative and respectful workplace that values every voice, celebrates what makes us unique and turns differences into innovation. Benefit from global and cross-business unit mobility, with development processes designed to ensure your professional growth. Utilize cutting-edge tools like Microsoft Copilot to enhance your productivity and efficiency. We are looking for a Data Scientist – Product Builder to join our Artificial Intelligence Center of Excellence within the Digital Hub. This is a role for someone who turns business problems into working data products, end to end. You will partner with our business areas (Construction, Highways, Airports, Energy, Digital Infrastructures and Headquarters)



to understand what really matters, dig deep into the data to find the answer, and then build the product that puts that answer in the hands of the people who need it. You will rely fully on agentic coding, working with AI coding agents as your main development partners to go from data analysis to a deployed, production-ready product in a fraction of the traditional time. You will not hand over a notebook and wait for someone else to turn it into a product: you own the problem, the analysis, the product and its adoption. The ideal candidate has spent a great deal of time working with real, messy business data, has a solid foundation in statistics, and combines business judgement with a strong sense of ownership and a builder's mindset. Own projects from start to finish: problem definition, data exploration, analysis, modelling, product build, deployment, adoption and continuous improvement. ~ Carry out in-depth exploratory and statistical analysis on large and heterogeneous datasets (operational, financial, asset, sensor or geospatial data) to uncover insights and support decision-making. ~ Apply sound statistical methods, such as hypothesis testing, experimental design, regression, time-series analysis, causal inference and uncertainty quantification, choosing the simplest approach that answers the business question. ~ Develop predictive and prescriptive models (machine learning, forecasting, optimisation)



when they add real value, validate them rigorously, and manage their lifecycle with MLflow (experiment tracking, model registry and versioning). ~ Use agentic coding as the core way of working, orchestrating AI coding agents to design, write, test, refactor and document code, and to build complete data products with a FastAPI back end and a Vue front end. ~ Review, validate and take full responsibility for agent-generated code, ensuring its quality, security, test coverage and maintainability. ~ Deploy and maintain products in containerised environments (Docker and Kubernetes), following good engineering practices such as version control, CI/CD and monitoring. ~ Communicate findings and results clearly to business teams and non-technical audiences, telling the story behind the data and measuring the business impact of each product. ~ Share agentic coding practices and learnings with the team, and actively participate in knowledge-sharing activities within the Digital Hub and the broader Technology & Innovation area. Bachelor's or Master's degree in Statistics, Mathematics, Computer Science, Engineering, Physics, Economics or a related quantitative field. ~ Minimum of 3 years of hands-on experience as a Data Scientist, Data Analyst or in a similar role, with an extensive track record of analysing real-world business data. ~ Strong foundation in statistics and probability, including inference, hypothesis testing, experimental design, regression and time series, and the ability to detect biases and assess how reliable a conclusion is. ~ Advanced programming skills for data analysis and statistical modelling in Python or R (for example pandas, scikit-learn or statsmodels in Python; t

📌 Data Scientist (España)
🏢 Ferrovial
📍 España