Regional Logistics Optimization — Operations Research Analyst

SHOPEE SINGAPORE PRIVATE LIMITED; Singapore; Sur place; SGD 65 000 - 90 000; Plein temps

Résumé du poste

SHOPEE SINGAPORE PRIVATE LIMITED is seeking an Operations Research Data Analyst to enhance logistics and supply chain efficiency across Southeast Asia. You will develop data-driven solutions, run simulations, and collaborate with teams to deliver scalable improvements in routes, warehousing, and inventory management.

The role focuses on building prototypes, iterating quickly, and applying practical constraints to models while communicating findings effectively to non-technical stakeholders.

Qualifications

• Bachelor’s or Master’s degree in a related field.
• Proficiency in Python for modelling and data analytics.
• At least 2 years of experience in operations research or data analytics in ecommerce/logistics.

Responsabilités

• Analyze data and build simulation models to improve logistics and supply chain processes.
• Optimize transportation routes and linehaul planning to reduce costs and improve delivery times.
• Improve fulfilment operations through warehouse layout, inventory management, and packaging efficiency.
• Lead or participate in projects, design implementation steps, and evaluate real-world effectiveness.
• Collaborate with cross-functional teams and communicate findings to stakeholders.
• Propose and implement continuous improvements to Shopee’s operational efficiency.

Connaissances

Python

Formation

Bachelor’s or Master’s degree in Operations Research, Industrial Engineering, Applied Mathematics, Statistics, Computer Science, or related field

Description du poste

SHOPEE SINGAPORE PRIVATE LIMITED is seeking an Operations Research Data Analyst to enhance logistics and supply chain efficiency across Southeast Asia. You will develop data-driven solutions, run simulations, and collaborate with teams to deliver scalable improvements in routes, warehousing, and inventory management.

The role focuses on building prototypes, iterating quickly, and applying practical constraints to models while communicating findings effectively to non-technical stakeholders.