Data Science Trainee
USA - CINTRA - Concession - I-66 - CI66-Manassas VA (VA0103), United States
Ferrovial
Welcome to the Ferrovial's website, global operator of sustainable infrastructure. Here you can find all the information about the company and subsidiaries.Develop your data driven skills to optimize our current operations and develop analysis to increase our knowledge for new development. Utilizing advanced analytics, you will work with the best in industry to optimize revenue and improve accuracy of Cintra and our concessions.
Summary of Duties and Responsibilities:
Develop and generate new ideas/projects for using Advanced Analytics with the two strategic goals:
Optimizing revenues in existing projects in operations
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
Support Cintra's North America 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
Required Qualifications:
Master’s degree in a quantitative field such as Operations Research, Data Science, Statistics, Civil or Industrial Engineering
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
Ethical, caring and with the ability to work in a collaborative environment
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: Data Analytics Engineering Finance Industrial Python R Research Spark SQL Statistics Tableau
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