Senior~Staff, Data Analyst (Catalog)

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

The Catalog team plays a pivotal role in delivering a seamless eCommerce experience, as it directly shapes how customers discover and purchase products online.

This role combines senior-level business analysis with a strong foundation in statistical methodology and data analytical expertise. The position focuses on turning vague business questions into measurable analytical problems, conducting hypothesis-driven deep dives, and delivering actionable insights to support business decision-making. The ideal candidate is comfortable performing advanced analytics (such as EDA, cohort analysis, and experimental design) while having practical familiarity with data systems and ETL pipelines to support their analytical workflows.

What You Will Do Advanced Analytics & Problem Solving -Turn vague business questions into structured, measurable analytical problems using hypothesis-driven analysis, root cause analysis, and systems thinking. -Conduct exploratory data analysis (EDA), time series analysis, segmentation/clustering, and cohort analysis to uncover business opportunities and solve complex catalog challenges. -Design and execute experiments, applying statistical inference, hypothesis testing, and sampling methodologies to validate business impacts. -Utilize Python/R and advanced analytics techniques (including feature engineering) to extract actionable insights from large-scale data.

Data Engineering & Infrastructure Support -Design, build, and maintain scalable ETL/ELT pipelines, data lake architecture, and API integration using Python and modern data warehouses (Snowflake/BigQuery). -Implement data quality checks, maintain core data tables/lineage, and optimize SQL queries to ensure backend reliability, performance, and self-serve analytics enablement.

Business Partnership & Solution Design -Collaborate closely with catalog and cross-functional business teams to translate requirements into data models, analytical frameworks, and dashboards. -Partner with external teams on special projects to investigate, diagnose, and mitigate business challenges through data.

Continuous Improvement -Stay current with evolving data technologies, tools, and industry best practices. -Proactively identify opportunities to enhance data infrastructure and analytical capabilities.

Basic Qualifications

Strong business analysis and problem-solving skills with the ability to turn vague business questions into measurable analytical problems using hypothesis-driven analysis and systems thinking.

Experience in advanced data analysis techniques using Python or R (EDA, feature engineering, time series analysis, cohort analysis, and segmentation/clustering).

Solid background in statistical methods, including experimental design, hyp