Ferrovial is looking to optimize its current operations and develop analysis to increase knowledge for new development in the highways business unit, Cintra, by utilizing advanced analytics to optimize revenue and improve accuracy of traffic and revenue forecasts.
Requirements
- Proficiency in Advanced Analytic Techniques
- High level of skill in SQL and/or Spark to process
- Experience in R and/or Python in implementing data science packages/routines
- Experience in Databases
- Knowledge with designing data visualizations and the utilization of software such as Tableau
Responsibilities
- Develop and generate new ideas/projects for using Advanced Analytics with the two strategic goals: Optimizing revenues in existing projects in operations and Improving accuracy of Traffic and Revenue forecasts by using new data sources and techniques to improve knowledge of main variables affecting the forecasts
- Develop, lead, and execute Data Analytics projects used either for Business Development activities (analysis of new projects) or for optimization of projects in Operations
- Support Advanced Analytic projects conducted by analytics teams at Cintra’s major projects (407 ETR in Toronto and DFW managed lanes)
- Support Cintra Europe and North American Traffic & Revenue teams when using Advanced Analytics for Traffic & Revenue studies
- Stay informed of new developments in Advanced Analytic techniques, systems, data sources, and providers and explore how to utilize them for the benefit of Cintra
Other
- Master’s degree in a quantitative field such as Operations Research, Data Science, Statistics, Civil or Industrial Engineering
- Ethical, caring and with the ability to work in a collaborative environment
- Global and cross-business unit mobility, with development processes designed to ensure professional growth
- Compelling benefits and employee wellbeing: Enjoy a comprehensive benefits package that rewards hard work and dedication
- 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
