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, hypothesis testing, statistical inference, and sampling methodologies.
• Advanced SQL skills with experience optimizing queries in modern data warehouses (e.g., Snowflake, BigQuery).
• Proven experience or familiar understanding in data engineering (ETL/ELT pipelines, data modeling, API integration, and pipeline optimization).
• Experience with data quality frameworks, monitoring tools, and ability to communicate technical/statistical concepts clearly to non-technical stakeholders.

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.

• Job titles and responsibilities may be subject to change depending on the candidate’s overall experience, etc. This will be communicated to the candidate at the appropriate time before the offer.

• Hiring may be restricted in case the legal qualifications required for hiring and work performance is not met.

• This is a full-time regular position and includes 12 weeks of probation period; provided, however, the probationary period may be either skipped, shortened or extended if necessary for business purposes.

Privacy Notice

· Your personal information will be collected and managed by Coupang as stated in the Application Privacy Notice located below. https://privacy.coupang.com/en/land/jobs/

Document Return Policy 

1. This notification is given pursuant to Article 11 (6) of the Fair Hiring Procedure Act.

2. A job applicant, who has applied but not been finally selected for a position at Coupang (the “Company”), may request the Company to return his/her hiring documents submitted pursuant to the Fair Hiring Procedure Act. However, this will not apply where the hiring documents were submitted via the website of the Company or e-mail, or where the job applicant submitted those documents voluntarily without a request from

the Company. In addition, if the hiring documents were destroyed due to a natural disaster or any other reasons not attributable to the Company, such documents will be deemed to have been returned to the job applicant.

3. A job applicant who wishes to request the return of his/her hiring documents pursuant to the main sentence of paragraph 2 above should fill out a “Request for Return of Hiring Documents” [Annex Form No. 3 in the Enforcement Rule of the Fair Hiring Procedure Act] and submit It by email (recruitingops@coupang.com). In such case, within fourteen (14) days from the date of identifying the receipt of the request, the Company will send the hiring documents to the job applicant’s designated address via registered mail. Please be informed that the job applicant is required to pay the postage on the registered mail.

4. In preparation for a job applicant’s request for the return of hiring documents pursuant to the main sentence of paragraph 2 above, the Company shall retain the original hiring documents submitted by the job applicant for 180 days from the completion of the recruiting process. If no request is made until the end of this period, all his/her hiring documents will be destroyed immediately in accordance with the Personal Information Protection Act.

5. The above paragraphs 1 - 4 shall only apply when the labor-related laws of Korea govern the application. They are otherwise not applicable.