• 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.