Ferrovial's Customer Analytics department is responsible for exploring and identifying future sources of competitive advantage by performing data and statistical analyses to address strategic business questions posed by management.
Requirements
- Proficiency in advanced analytical techniques such as regression, classification, clustering, tree-based methods, and optimization models.
- Experience performing statistical analysis of controlled experiments.
- Experience using SQL and/or Spark to process, clean, and analyze large datasets.
- Experience with R and/or Python.
- Experience working with Databricks.
Responsibilities
- Develop revenue optimization strategies for existing toll concessions.
- Build models to accurately forecast traffic and revenue using existing and new data sources and analytical techniques; identify key variables affecting forecasts through machine learning and statistical analysis.
- Design experiments and develop/execute measurement plans to evaluate new initiatives in a test & learn environment.
- Stay informed of new developments in analytics techniques, systems, data sources, and providers, and evaluate opportunities to apply them to benefit Cintra.
Other
- Advanced degree (M.S. or Ph.D.) in quantitative fields such as Operations Research, Data Science, Statistics, Computer Science, Industrial Engineering, or a related discipline from an accredited institution.
- 1–3 years of experience building advanced analytical models that demonstrate measurable business impact.
- A research-oriented and innovative mindset—curious, proactive, and eager to explore new ideas.
- Strong written and verbal communication skills, particularly in technical report writing.
- Ability to summarize, present, and explain findings and conclusions to management.
- Strong task management skills and the ability to meet strict deadlines independently and in an organized manner.
- Ability to collaborate effectively within a self-managed team structure.
