Company Introduction We exist to wow our customers. We know we’re doing the right thing when we hear our customers say, “How did I ever live without Coupang?” Born out of an obsession to make shopping, eating, and living easier than ever, we are collectively disrupting the multi-billion-dollar commerce industry from the ground up and establishing an unparalleled reputation for being leading and reliable force in South Korean commerce. We are proud to have the best of both worlds — a startup culture with the resources of a large global public company. This fuels us to continue our growth and launch new services at the speed we have been since our inception. We are all entrepreneurs surrounded by opportunities to drive new initiatives and innovations. At our core, we are bold and ambitious people that like to get our hands dirty and make a hands-on impact. At Coupang, you will see yourself, your colleagues, your team, and the company grow every day. Our mission to build the future of commerce is real. We push the boundaries of what’s possible to solve problems and break traditional tradeoffs. Join Coupang now to create an epic experience in this always-on, high-tech, and hyper-connected world. Role Overview As a Principal Data Scientist within Coupang’s Supply Chain Management Autonomation (SCMA) organization, you will serve as the scientific authority and primary architect for our Cognitive Engine. You will be the bridge between cutting-edge Deep Learning (signal sensing) and Operations Research (constraint-based optimization). Your mission is to transform Coupang’s supply chain into a durable competitive advantage by building a fully autonomous, agentic operating system that is capable of multi-step reasoning, where LLMs interpret signals and OR models execute procurement decisions without manual intervention. This system will manage procurement decisions for 10M+ units daily, with the goal of reducing manual execution by 50% while maximizing inventory ROI and in-stock rates. Key Responsibilities Architect the Cognitive Engine: Lead the synthesis of Large Language Models (LLMs), Knowledge Graphs (KGs), and Graph Neural Networks (GNNs) to create an autonomous, agentic supply chain platform. Integrate DL & OR: Design hybrid systems that utilize Deep Learning for high-fidelity signal sensing and Operations Research for complex, constraint-based optimization. Drive Full Autonomy: Develop models that proactively manage the entire SKU lifecycle at hyper-scale, moving from "human-in-the-loop" to "human-on-the-loop" strategic oversight. Establish Model Governance: Implement strict governance frameworks to ensure high-stakes autonomous decisions remain accurate, unbiased, explainable, and resilient to data drift. Simulate & Experiment: Lead Large-scale Discrete Event Simulations (DES) and Agent-Based Simulation models to validate "what-if" scenarios before production deployment. Strategic Leadership: Advise leadership on the research roadmap and technical breakthroughs that will define the future of e-commerce supply chain management . Cross-Functional Partnership: Partner with SCMA Engineering to deploy production-grade models that handle extreme demand volatility without compromising latency or reliability. Qualifications & Technical Requirements Education: Ph.D. or Master’s in Operations Research, Computer Science (AI/ML focus), or a related quantitative field. Experience: 10+ years of relevant industry experience, ideally in e-commerce, SCM, or high-complexity trading environments. AI/ML Expertise: Hands-on experience designing and implementing: Model Architectures: Experience with state-of-the-art time-series and graph architectures (e.g., TiDE, GNNs, Transformers), and experiences in Reinforcement learning models. Generative AI: Expert-level knowledge of LLMs and Agentic workflows. Graphs: Knowledge Graphs and Graph Neural Networks (GNNs) for supply chain mapping. Optimization & Heuristics: Deep proficiency in Mixed-Integer Programming (MIP), Dynamic Programming, and Meta-heuristics (Genetic Algorithms, PSO). Simulation Mastery: Proven track record in Discrete Event Simulation or Agent-Based modeling (e.g., AnyLogic, Simio). Tooling: Solvers: Expertise in Gurobi, Cplex, or SCIP. Languages: Python, Java, or Scala. Data: SQL mastery and experience with Big Data environments (Spark, Clickhouse). Recruitment Process and Others Recruitment Process Application Review - Phone Interview - Onsite (or Virtual Onsite) Interview – Offer The exact nature of the recruitment process may vary according to the specific job and may be changed due to scheduling or other circumstances. Interview schedules and the results will be informed to the applicant via the e-mail address submitted at the application stage. Details to Consider This job posting may be closed prior to the stated end date for application if all openings are filled. Coupang has the right to rescind an offer of employment if a candidate is found to have submitted false information as part of the application process. Those eligible for employment protection (recipients of veteran’s benefits, the disabled, etc.) may receive preferential treatment for employment in accordance with applicable laws. 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