Senior Data Scientist, Geospatial & Mobility Analytics

Senior Data Scientist, Geospatial & Mobility Analytics

About the role

Advanced Analytics is an important capability for identifying new sources of competitive advantage at Cintra. The Senior Data Scientist will use geospatial analytics, mobility data, external data, and advanced analytical methods to address strategic business questions posed by management. The Senior Data Scientist will help define the analytical approach for each project, identify the appropriate internal and external data, and translate findings into clear business conclusions and recommendations. Responsibilities will also include supporting other analytics and Traffic & Revenue teams and staying current on emerging methods, data sources, and technologies. Although based in Austin, Texas, this person will support projects and teams across North America and Europe.

Key responsibilities

• Execute Advanced Analytics projects with three strategic goals:

• o Optimize traffic and revenue performance at existing projects.

• o Improve Traffic & Revenue forecasts by using new data and analytical techniques to better understand the main factors affecting demand and revenue.

• o Support Business Development activities and the analysis of new projects.

• Conduct geospatial and mobility analysis to understand travel patterns, route choice, customer behavior, network conditions, and external demand drivers.

• Identify, evaluate, and integrate external data sources, including connected-vehicle, mobile-device, routing, demographic, land-use, economic, weather, and event data.

• Support Advanced Analytics projects conducted by Cintra’s major projects and Traffic & Revenue teams in North America and Europe.

• Translate complex analysis into clear conclusions, recommendations, visualizations, and presentations for management.

• Stay informed about developments in geospatial analytics, mobility data, AI, external-data providers, and advanced analytical techniques.

Qualifications

• To perform this job successfully, an individual must be able to perform each essential duty satisfactorily. The requirements below are representative of the knowledge, skills, and abilities required to fulfill those duties. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.

Key Requirements:

• Master’s degree in Data Science, Statistics, Computer Science, Geographic Information Science,
• Transportation, Operations Research, Engineering, Economics, or a related quantitative field.
• 3 to 6+ years of relevant professional experience in data science, geospatial analytics, mobility analytics, transportation analytics, or a related field.
• Strong proficiency in Python and SQL, with experience using Databricks, Spark, or similar cloud-based analytics platforms to process and analyze large, complex, and imperfect datasets.
• Experience applying statistical analysis, machine learning, predictive modeling, and exploratory analytical methods to real-world business problems.
• Experience with geospatial or mobility analytics, including spatial data, trip or trajectory data, origin-destination analysis, route analysis, or transportation networks.
• Experience with tools such as GeoPandas, PostGIS, ArcGIS, QGIS, or comparable geospatial technologies.
• Ability to independently structure business questions, select appropriate data and methods, and develop defensible analytical conclusions.
• Experience developing clear visualizations and communicating analytical findings and business implications to management.

Desirable Skills and Experience:

• Experience working with connected-vehicle, mobile-device, routing, transaction, demographic, land-use, weather, event, economic, or similar external data.
• Experience in transportation, toll roads, managed lanes, mobility, infrastructure, logistics, or location intelligence.
• Exposure to route choice, pricing, revenue management, customer behavior, or Traffic & Revenue forecasting.
• Experience with cloud-based data platforms, Git, and reproducible analytical workflows.

Professional Qualities:

• Curious, research-oriented, and willing to explore new questions, data sources, and analytical approaches.
• Strong written and verbal communication skills, including the ability to explain technical findings in clear business language.
• Able to summarize finding