Description : About the role 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.
What makes this role different is how you build.
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 idóneo 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.
Key Responsibilities Work closely with business stakeholders to frame business problems, identify the questions that matter and translate them into clear objectives and measurable success metrics.
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 tidyverse, data.table or tidymodels in R), and strong SQL skills.




Demonstrable experience building products end to end with agentic coding tools such as GitHub Copilot (agent mode), Claude Code, Cursor, Codex, Devin or similar.
A portfolio of products or projects built this way will be highly valued.
Experience building and shipping data products with FastAPI for the back end and Vue for the front end.
Ability to turn ambiguous business problems into concrete analytical approaches and useful products, with strong business acumen and product sense.
Solid software engineering fundamentals: Git, testing, code review and CI/CD.
Hands-on experience with MLflow for experiment tracking, model registry and model lifecycle management.
Basic working knowledge of Docker and Kubernetes, enough to deploy, monitor and troubleshoot applications (deployments, services, logs).
Ownership, autonomy, initiative and a bias for action; comfortable taking a project from zero to production.
Excellent communication skills and the ability to document and present work for both technical and non-technical audiences.
High level of English; a minimum C1 level is required.
Seize the challenge.
Move the world together
Innovative, creative, respectful, and diverse are some of the ways we describe ourselves.
We are motivated by challenges, and we collaborate across our business units to move the world together.
Your journey to a fulfilling career starts here
Ferrovial is an equal opportunity employer.
We treat all jobs applications equally, regardless of gender, color, race, ethnicity, religion, national origin, age, disability, pregnancy, sexual orientation, gender identity and expression, covered veteran status or protected genetic information (each, a "Protected Class"), or any other protected class in ac

📌 Data Scientist – Product Builder (Madrid)
🏢 Ferrovial
📍 Madrid