Transportation Senior Data Scientist, Transportation Tactical Management (TTM)

The Transportation Data Scientist is responsible for leveraging data analytics and machine learning techniques to gain insights and drive decision-making for transportation-related challenges. This role involves working closely with all miles from transportation, planning areas, and engineering teams to identify, collect, and analyze relevant data to uncover patterns, trends, and predictions that can optimize transportation systems and services.

Key job responsibilities
Collaborate with cross-functional teams to understand transportation challenges and identify data sources that can provide valuable insights
Design and implement data collection, processing, and storage pipelines to gather and manage large-scale transportation data (e.g., traffic sensor data, vehicle telematics, rideshare data, infrastructure utilization, etc.);

Develop advanced analytical models and machine learning algorithms to analyze transportation data and generate predictive insights (e.g., demand forecasting, route optimization, infrastructure maintenance planning, etc.)

Visualize and present data-driven insights and recommendations to stakeholders, including transportation miles (ATS, AMZL, 3P carriers and Air), operations teams, and decision-makers.

Stay up-to-date with the latest trends, technologies, and best practices in transportation data science and analytics;

Contribute to the development and improvement of the organization’s transportation data strategy and capabilities.

Basic Qualifications

– Data scientist experience;
– Experience with data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.);
– Experience with statistical models e.g. multinomial logistic regression.
– English skills for conversation.

Preferred Qualifications

– Experience with data visualization using AWS QuickSight, Tableau, R Shiny, etc;
– Knowledge of AWS tech stack (e.g., AWS Redshift, S3, EC2, Glue);
– Experience as a leader and mentor on a data science team;
– Experience in optimization models for transportation
– Experience working in the transportation industry or with transportation agencies
– Familiarity with cloud-based data processing and storage technologies
– Demonstrated ability to work in a collaborative, cross-functional team environment.