Job Description

• Support day-to-day logistics operations through data analysis and operational reporting, while continuously learning how data is used to drive operational decisions. • Learn to build and improve analytical models related to workforce efficiency, hub performance, and site evaluation, with guidance from senior team members. • Participate in developing, testing, and maintaining data tools or scripts that support operational workflows such as parcel sorting, routing, and productivity tracking. • Collect, clean, and analyze logistics data (e.g., volume, on-time performance, labor hours) to identify trends, issues, and improvement opportunities. • Actively collaborate with operations and management teams to understand business processes and gradually translate operational needs into data-driven solutions. • Continuously improve understanding of logistics operations, data systems, and KPIs through hands-on work, feedback, and self-driven learning. • Assist in preparing dashboards, reports, and presentations to clearly communicate operational insights and performance metrics.

Requirements

• Bachelor’s or Master’s degree in Data Science, Computer Science, Logistics, Business Analytics, or a related field. • Strong learning mindset and curiosity, with motivation to continuously develop technical, operational, and business skills. • Comfortable working with data and willing to learn how to identify patterns, risks, and improvement opportunities. • Interest in logistics or warehouse operations; prior exposure is a plus but not required. • Ability to take feedback well, adapt quickly, and grow into more independent analytical responsibilities over time. • Foundational programming skills in Python, R, or SQL; experience from coursework, projects, internships, or entry-level roles is acceptable.