Job Overview

Global Operations Technology organization is responsible for the systems that enable Coupang to reliably deliver to customers within hours of orders being placed. Global Ops Tech is on a mission to innovate logistics by building an efficient delivery network at breakthrough scale and speeds. As a Data Scientist, you will leverage advanced algorithms to improve Coupang’s customer experience by ensuring ultra-fast deliveries are on time even during the busiest times of the year. We are looking for a Scientist that can drive the direction of technology across multiple teams, leverage deep industry knowledge and use statistical and machine learning techniques to bring value to customers. The ideal candidates are pragmatic, resourceful, and embrace challenges that are seemingly impossible. The ideal candidates also have rich industry experience and a track record of delivering highly impactful projects.

Basic Qualifications

• Masters degree in a quantitative discipline: statistics, operations research, computer science, informatics, engineering, applied mathematics, economics or equivalent experience.
• 8+ years of experience in solving complex problems in the area of operations research and developing strategies for large-scale supply chain, transportation and logistic networks.
• Perform quantitative, economic, and numerical analysis of the performance of large-scale systems under uncertainty using statistical and optimization tools such as Python, R and Xpress/Gurobi/CPLEX/etc to determine optimal and heuristic solution strategies for optimization problems.
• Apply theories of mathematical optimization, including linear programming, combinatorial optimization, integer programming, dynamic programming, network flows and algorithms to design optimal or near optimal solution methodologies to be used by in-house decision support tools and software.
• Excellent written and verbal communication skills while addressing both technical and business people; ability to speak at a level appropriate for the audience. The ideal candidate should be able to present business cases, and document models, analyses, and results to influence important decisions

Preferred Qualifications

• PhD degree in a quantitative discipline: statistics, operations research, computer science, informatics, engineering, applied mathematics, economics, etc.
• 5+ years of hands-on experience applying theoretical models in an applied environment.
• Experience in supply chains, transportation and logistics, and network optimization models.
• Proficiency in model development, model validation and model implementation for large-scale applications