Transportation Analyst

Cambridge Systematics

About The Position

Cambridge Systematics’ Analytics business unit researches, develops, and applies practical decision-support tools, including transportation models. The Transportation Analyst contributes to tools supporting travel demand modeling, asset management, operations and performance monitoring, transit planning, location-based services analytics, and other disciplines. Working across teams with subject-matter and technical experts, the Analyst develops and engineers scalable, repeatable data processing, analysis, and visualization solutions that turn messy data into actionable insights. The role may also contribute to business development and project management activities.

Requirements

Bachelor’s degree in Transportation Engineering, Computer Science, Data Analytics, Applied Statistics, Data Science, or a related field.
0–4 years of applicable experience.
Intermediate Python programming capabilities.
Proficiency in SQL and database technologies, including knowledge of data modeling and data warehousing principles.
Experience with data visualization software such as Tableau or Power BI.
Ability to collaborate effectively using Git/GitHub.
Excellent oral and written communication skills.

Nice To Haves

Master’s degree in Transportation Engineering, Computer Science, Data Analytics, Applied Statistics, Data Science, or a related field.
Experience managing analytics in an enterprise environment.
Experience developing production-ready code and applying it in the cloud.
Experience with one or more cloud-based analytics platforms such as Databricks, Snowflake, BigQuery, or Fabric.
Ability to build scalable data pipelines with modern technologies such as Airflow, Dagster, and dbt.
Working knowledge of continuous-integration/continuous-delivery systems.
Front-end development experience using JavaScript frameworks.

Responsibilities

Analyze requirements to understand their technical and business implications.
Design and implement database solutions to support projects and tools.
Design data analysis and data engineering methods that meet current needs while allowing for likely future needs.
Develop production-ready code for application in the cloud.
Provide clear, concise, and thorough documentation as required.
Produce thorough, polished, high-quality work that reflects well on the company.
Apply the technical skills necessary to complete assignments effectively and efficiently.
Adapt quickly to new project contexts and learn new tools and technologies.
Identify opportunities to address client requirements through innovative data analysis and data engineering solutions.
Learn new tools and technologies as appropriate.
Potentially contribute to business development and project management activities.