Data Scientist - Transportation and Fleet Analytics

Company Overview

Company details not provided.

Job Summary

The Data Scientist will play a pivotal role in analyzing large-scale transportation and fleet data to derive actionable insights that enhance operational efficiency. This position involves leveraging data science techniques to build predictive models and optimization algorithms, thus contributing to the overall improvement of logistics and supply chain management.

Responsibilities

• Analyze large-scale transportation and fleet data (e.g., GPS logs, Transportation Management System (TMS) data, fuel usage) to uncover patterns, trends, and areas for improvement.
• Build predictive models for Estimated Time of Arrival (ETA), vehicle maintenance, and fuel consumption forecasting.
• Design and implement optimization algorithms for route planning, vehicle dispatch, and fleet allocation.
• Develop real-time dashboards and visualizations to monitor key logistics Key Performance Indicators (KPIs).
• Collaborate with cross-functional teams across Supply Chain, Logistics, and IT to transform business needs into actionable data science solutions.
• Ensure high data quality and build scalable data pipelines to support analytics initiatives.

Qualifications

• Proficiency in Python for data manipulation, modeling, and visualization.
• Experience in transportation, logistics, or fleet management domains is highly preferred.
• Strong understanding of machine learning, statistical modeling, and operations research.
• Ability to work with large, complex datasets and cloud-based data environments.
• Excellent communication and problem-solving skills.

Preferred Skills

• Knowledge of data visualization tools and techniques.
• Familiarity with database management systems.
• Experience with additional programming languages (e.g., R, SQL).

Experience

Details regarding minimum experience required not specified; however, experience in relevant domains is preferred.

Environment

Typical work setting not specified; details regarding remote, in-office, or hybrid environments are not provided.

Salary

Salary information not provided.

Growth Opportunities

Opportunities for career advancement within the company not specified.

Benefits

Benefits offered not specified.