Coupang is one of the largest and fastest growing e-commerce platforms on the planet. We are on a mission to revolutionize everyday lives for our customers, employees and partners. We solve problems no one has solved before to create a world where people ask, “How did we ever live without Coupang?” Coupang is a global company with offices in Beijing, Los Angeles, Seattle, Seoul, Shanghai, and Silicon Valley.
This role is part of the SCM Autonomation team at Coupang. As an Data Scientist, you will be at the forefront of building machine learning and/or deep learning models that drive supply chain efficiencies and innovations.
Location: Beijing, China/Shanghai, China
Who We Are?
Supply Chain Automation is responsible for predicting what customers want to buy and automating the inventory ordering process. TIP/ROQ is our key system to support Coupang core network and Fresh daily ordering. The target is to manage all Coupang FCs inbound. We use cloud computing, data analysis, machine learning to improve our operation efficiency.
How We Do It?
We use OR/Machine Learning/Deep Learning/LLM processes to Support Operation team inventory planning and generate our daily Vendor Order recommendation. We focus on achieving higher end customer experience within budeget and all kinds of constraints. We provide the Data Science team with ML Engineer and Data Analysis resources to ensure the Data Scientists can focus on building the best models. Our goal is to apply cutting edge models into our production environments, using a deep understanding of the e-commerce business domain to demonstrate results in production. We join big thinking with a pragmatic approach to measuring results.
Our systems are built on Hadoop and Spark in Cloud environments, with Deeplearning, Large language Model and OR model implemented. Data Scientists work with a cross-functional team of ML Engineers, Back-end Engineer, Analysts and Product Owners to build world-class systems that keep our Supply Chain running smoothly.
Responsibilities:
- Develop and implement OR/DL/LLM models to predict inventory needs and optimize stock levels.
- Analyze large datasets to identify trends, patterns, and insights that can improve inventory management.
- Utilize large language models (LLMs) to enhance predictive analytics and decision-making processes.
- Design and develop knowledge graphs to represent SKU, vendor, and operational data, facilitating better understanding and management of inventory.
- Collaborate with cross-functional teams to understand business requirements and translate them into data-driven solutions.
- Design and execute experiments to validate model performance and improve accuracy.
- Create and maintain documentation for data science projects, including methodologies, code, and results.
- Present findings and recommendations to stakeholders in a clear and actionable manner.
What are the things this person MUST do/have?
- Master's or Ph.D. in Data Science, Computer Science, Statistics, or a related field.
- Proven experience in developing and deploying machine learning models, particularly in inventory planning or supply chain management.
- Strong proficiency in programming languages such as Python, Familiar with Big data processing and handling
- Experience with large language models (LLMs) and natural language processing (NLP).
- Excellent analytical and problem-solving skills.
- Ability to work independently and as part of a team.
- Strong communication skills, both written and verbal.
Essential Qualifications
- 8+ years of experience in ML/DL/LLM modeling or algorithm areas, with significant expertise in SCM or related fields.
- Familiarity with database management and SQL.
- Experience with data engineering and ETL processes.
- Understanding of supply chain dynamics and vendor management.
- Familiarity with knowledge graph construction and graph databases (e.g., Neo4j, RDF)
