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[쿠팡FTS] Director, Data science engineering

Location Seoul, South Korea


Coupang is creating a new shopping experience to impress each and every customer, from the moment a customer opens the Coupang app to the moment the product is delivered to the door. With an outstanding end-to-end e-commerce and logistics network, and a culture that is stubbornly customer-focused, Coupang has never sacrificed speed, selection or price. Now Coupang has revolutionized the delivery of millions of products, including fresh food, delivered nationwide, 365 days a year, in just a few hours. All of these are Coupang’s efforts for millions of customers in the Korean e-commerce market. Korea is a market with larger and faster-growing e-commerce opportunities than any other country in the world.


Job Overview:
Global Operations (GO) is a department in Coupang operating Order Fulfillment, Inventory and Logistics to ensure a fast and high-quality delivery service to Coupang’s customers. The GO Data Science group builds machine learning and optimization models/algorithms and manages end-2-end data science solutions to solve business problems with complex rules and conflicting objectives, such as labor planning, task scheduling, fulfillment center picking/stowing optimization, operational anomaly detection and transportation routing. The Data Science Engineering team within GO Data Science develops, deploys and maintains the group’s production algorithms - at the scale required by Coupang’s fast-moving fulfillment business.


Key Responsibilities:

  • People leadership: Manage, mentor and grow an international team of back-end and machine learning engineers 
  • Enable efficient collaboration with data scientists, product owners and software engineers to address fulfillment center business needs, improve logistics processes, help cut operation cost, and optimize customer experiences
  • Lead the implementation and operation of a platform that facilitates training data science algorithms and deploying machine learning models at scale
  • Oversee the development of services enabling the automation of data science pipelines from data access to model deployment into production
  • Work together with domain engineering teams and their managers when integrating analytical models built by the team into domain applications
  • Drive the team’s technical direction and strategy while shaping long-term vision and architecture
  • Lead and continuously improve development processes of the team, setting a high bar for engineering excellence 


Basic Qualifications:

  • Masters degree in Computer Science or another equivalent discipline
  • A passion for people management and employee mentorship 
  • 5+ years of hands-on experience in software development including design, infrastructure and application development, debugging and support with a focus on backend engineering
  • 3+ years of experience managing engineering teams with a focus on data science and machine learning engineering
  • Expert knowledge of one or more of the following programming languages: Java, Python and C++ and required tools to develop, debug and optimize code
  • Advanced knowledge of distributed data computing tools such as Hive, Spark and Kafka
  • Advanced knowledge of relational database systems
  • Experience optimizing resource intensive algorithms for performance in production
  • Experience working in an agile scrum/development process
  • Good written English communication skills

Preferred Qualifications:

  • 2+ years of experience developing Docker-based systems using Kubernetes or equivalent technology
  • Advanced knowledge of cloud technology solutions on either AWS, Azure, Google Cloud
  • Knowledge of data science and machine learning fundamentals
  • Knowledge of fulfillment center operations, logistics or supply chain management
  • Very good communication skills in English, written and verbal