Operations & Data Analytics Intern, Regional SPX Express (Summer 2026)

About The Team E-commerce supply chains are among the most dynamic and complex systems in the world. Every click, every order, and every delivery triggers thousands of operational decisions across warehouses, transportation networks, routing systems, and last-mile operations.

Job Description As an Operations & Data Analytics Intern, you will work at the heart of this ecosystem — using data to uncover inefficiencies, diagnose root causes, and fix real operational problems across the end-to-end supply chain.

You will deep-dive into ambiguous issues, challenge assumptions, and design scalable, pragmatic solutions that can be implemented on the ground. Your work will directly influence how millions of parcels move across the region.

You will also partner with Shopee’s 8 markets to understand local nuances and operational constraints — adapting regional frameworks into scalable, practical solutions across diverse market environments.

If you are someone who enjoys figuring out why things break, gets energised by solving messy real-world problems, and wants to see your solutions drive tangible impact, this role is for you.

• Analyse large, complex datasets using Python and SQL to identify inefficiencies and performance gaps
• Deep-dive operational issues to uncover root causes — not just symptoms Build analytical models, automation scripts, and dashboards to support decision-making
• Propose and drive scalable, pragmatic solutions that can be executed across markets
• Work closely with operations, product, and tech teams to turn insights into real-world fixes
• Collaborate with regional and local stakeholders to adapt solutions based on market-specific realities
• Measure impact post-implementation to ensure sustainable improvements.

Requirements

• Currently pursuing a degree in any discipline with a strong analytical component (e.g., quantitative, technical, or data-driven fields)
• Willing to commit a 3 months full time internship
• Proficiency in Python and/or SQL
• Strong analytical skills and comfort working with large, messy datasets
• Innately curious and motivated to understand problems deeply
• A natural problem-fixer — someone who is not satisfied highlighting issues, but is driven to solve them
• Structured thinker who can break down complexity into actionable steps
• Self-driven, hands-on, and comfortable operating in ambiguity
• Strong communication skills and ability to work across diverse stakeholders