Sr~Staff Data Analyst (Coupang Eats)
Location: Seoul, South Korea
Department: Eats Tech
Eats Analytics ํ ์๊ฐ ๐
Eats Analytics ํ์ ๋น์ ์ย ๋ฐ์ดํฐ, ๋ถ์, ๊ทธ๋ฆฌ๊ณ ์ ์ฉํ AI๋ฅผ ํตํด ๋ณต์กํ ๋น์ฆ๋์ค ๋ฌธ์ ๋ฅผ ํด๊ฒฐํจ์ผ๋ก์จ, Coupang Eats์ ๋ชจ๋ ์์ฌ๊ฒฐ์ ์ดย ๋ฐ์ดํฐ์ ๊ธฐ๋ฐํ๊ณ ์ค์ง์ ์ธ ์ํฉํธ๋ฅผ ์ฐฝ์ถํ๋๋กย ๋ง๋๋ ๊ฒ์ ๋๋ค.
์ฐ๋ฆฌ ํ์ ๋จ์ํ ๋ฆฌํฌํ ์ด๋ ์ด์ ์ง์์ ๋์ด์ญ๋๋ค. ๋น์ฆ๋์ค, ํ๋ก๋ํธ, ์ด์ ๋ฆฌ๋๋ค๊ณผ ๊ธด๋ฐํ๊ฒ ํ์ ํ์ฌ ๋ฌธ์ ๋ฅผ ์ ์ํ๊ณ , ๋ถ์ ๋ฐ ๋ฐ์ดํฐ ๋ชจ๋ธ์ ๊ตฌ์ถํ๋ฉฐ, ์ธ์ฌ์ดํธ๋ฅผ ๋๊ท๋ชจ๋ก ์ด์์ ์ ์ฉํฉ๋๋ค.
Coupang Eats์ ๋ฐ์ดํฐ ๋ถ์์ย ๋น์ฆ๋์ค ์ ๋ต, ์คํ(Experimentation), ์์ธก(Forecasting), ๊ทธ๋ฆฌ๊ณ AI ๊ธฐ๋ฐ ์์ฌ๊ฒฐ์ ย ์ ๋ฐ์ ๊ฑธ์ณ ์์ผ๋ฉฐ, ํ์๋ค์ Data Science, Machine Learning, ํน์ ๊ณ ๊ธ ๋น์ฆ๋์ค ์ ๋๋ฆฌํฑ์ค ์ญํ ๋ก ์ฑ์ฅํ ์ ์๋ ๊ธฐํ๋ฅผ ์ป๊ฒ ๋ฉ๋๋ค.
Data Analyst๋ก์ ๋น์ ์ย ๋ฌธ์ ์ ์๋ถํฐ ๋ชจ๋ธ ๊ธฐ๋ฐ ์ธ์ฌ์ดํธ ๋์ถ, ์ค์ ์ด์ ์คํ๊น์ง ์๋ํฌ์๋๋ก ๊ด์ฌํ๊ฒ ๋๋ฉฐ, ๋๊ท๋ชจ ๋ฐ์ดํฐ, ์คํ ํ๋ซํผ, AI ๊ธฐ๋ฐ ๋น์ฆ๋์ค ํ์ฉ ์ฌ๋ก๋ฅผ ํญ๋๊ฒ ๊ฒฝํํ๊ฒ ๋ฉ๋๋ค.
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์ฃผ์ ์ ๋ฌด ๐
- ๋ฐฐ๋ฌ ์ด์, ๋จธ์ฒํธ ์ํ๊ณ, ๊ณ ๊ฐ ์ฑ์ฅ, ๋ง์ผํ๋ ์ด์ค ๊ตฌ์กฐ ์ ๋ฐ์ ๊ฑธ์ณ ๋ฐ์ดํฐยท๋ถ์ยท์ ์ฉํ AI๋ฅผ ํ์ฉํ์ฌ ๋ค์ํ ๋น์ฆ๋์ค ๋ฌธ์ ํด๊ฒฐ
- ๋ชจํธํ ๋น์ฆ๋์ค ์ง๋ฌธ์ ๋ถ์ ํ๋ ์์ํฌ์ ๋ฐ์ดํฐ ๋ชจ๋ธ๋ก ๊ตฌ์กฐํํ๊ธฐ ์ํด ๋น์ฆ๋์ค ๋ฐ ํ๋ก๋ํธ ๋ฆฌ๋์ ํ์
- ๋๊ท๋ชจ A/B ํ ์คํธ์ ์คํ์ ์ค๊ณ, ์คํ, ๋ถ์ํ๋ฉฐ ๋จ๊ธฐ ์ฑ๊ณผ์ ์ฅ๊ธฐ ๋น์ฆ๋์ค ์ํฅ ํ๊ฐ
- ์ด์ ๋ฐ ์ ๋ต์ ์์ฌ๊ฒฐ์ ์ ์ง์ํ๋ ๋ถ์ ๋ฐ์ดํฐ์ , ํ์ดํ๋ผ์ธ, ๋ชจ๋ธ(์: ์์ธก, ์ต์ ํ, ์ธ๊ทธ๋ฉํ ์ด์ ) ๊ฐ๋ฐ ๋ฐ ์ ์ง
- ํต๊ณ ๋ถ์, ๋ชจ๋ธ๋ง, ์คํ์ ํตํด ๋ฐฐ๋ฌ ์๊ฐ, ๋น์ฉ ํจ์จ, ์์โ๊ณต๊ธ ๊ท ํ, ๊ณ ๊ฐ ์ ์ง์จ ๋ฑ ํต์ฌ ๋น์ฆ๋์ค ์งํ ์ต์ ํ
- ๋ชจ๋ธ๊ณผ ์ธ์ฌ์ดํธ๋ฅผ ์ผ์์ ์ธ ์์ฌ๊ฒฐ์ ํ๋ก์ธ์ค์ ์ ์ฉํ์ฌ ์ด์ ํจ์จ์ฑ์ ๋์ด๊ณ , ๋ถ์ ๋ฐฉ๋ฒ๋ก ์ ์ง์์ ์ผ๋ก ๊ฐ์
- ๋จ์ํ ๊ณผ๊ฑฐ ๋ฆฌํฌํ ์ด ์๋ย ๋ฏธ๋์งํฅ์ ์ธ์ฌ์ดํธ ์ ๊ณต๊ณผ ํต์ฌ ์งํ ์ค๋์ญ ํ๋ณด
- ๊ณ ๊ฐ, ๋จธ์ฒํธ, ์ด์ ๋ฐ์ดํฐ๋ฅผ ์ฌ์ธต ๋ถ์ํ์ฌ ํ์ฅ ๊ฐ๋ฅํ ์ฑ์ฅ ๊ธฐํ ๋ฐ๊ตด
- ๊ธฐ์ ์ ๋ฐฐ๊ฒฝ์ด ์๋ ์ดํด๊ด๊ณ์์๊ฒ๋ ๋ช ํํ๊ฒ ์ธ์ฌ์ดํธ์ ์ ์์ ์ ๋ฌํ๋ฉฐ, ๋ค์ํ ์กฐ์ง ๋ ๋ฒจ์ ์์ฌ๊ฒฐ์ ์ ์ํฅ๋ ฅ ํ์ฌ
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ํต์ฌ ์ฑ๊ณผ ์งํ (KPI)
- ๋ถ์, ์คํ, ๋ชจ๋ธ์ ํตํด ์ฐฝ์ถ๋ย ์ค์ง์ ์ธ ๋น์ฆ๋์ค ์ํฉํธ
- ๊ณ ๊ฐ, ๋จธ์ฒํธ, ์ด์ ๊ด๋ จ KPI ๊ฐ์ (์ ์ง์จ, ํจ์จ์ฑ, ์ ๋ ์ด์ฝ๋ ธ๋ฏน์ค ๋ฑ)
- ์ผ์ ์ด์์์ ๋ถ์ ๋ชจ๋ธ๊ณผ ์ธ์ฌ์ดํธ์ ํ์ฉ๋ ๋ฐ ํจ๊ณผ์ฑ
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์๊ฒฉ ์๊ฑด ๐
- ๋น์ฆ๋์ค ๋ฌธ์ ํด๊ฒฐ์ ์ํด ๋ฐ์ดํฐ ๋ถ์, ์ ๋๋ฆฌํฑ์ค, ๋๋ ๋ฐ์ดํฐ ์ฌ์ด์ธ์ค๋ฅผ ์ ์ฉํย 5๋ ์ด์์ ๊ฒฝ๋ ฅ
- SQL์ ๋ํ ๊ฐํ ์๋ จ๋์ ETL, ๋ฐ์ดํฐ ๋ชจ๋ธ๋ง, ๋๊ท๋ชจ ๋ฐ์ดํฐ์ ๊ฒฝํ
- ํน์ ๋น์ฆ๋์ค ๋๋ฉ์ธ, ํ๋ก๋ํธ ์์ญ, ๋๋ ์ด์ ๊ธฐ๋ฅ์ ๋ํ ๋ถ์ ์ค๋์ญ ๊ฒฝํ
- ๋ฐ์ดํฐ ์ธ์ฌ์ดํธ๋ฅผ ๋น์ฆ๋์ค ์ฑ๊ณผ๋ก ์ฐ๊ฒฐํ ์ ์๋ ๋ฐ์ด๋ ๋ถ์์ ์ฌ๊ณ ๋ ฅ
- ๋น ๋ฅด๊ฒ ๋ณํํ๊ณ ๋ถํ์คํ ํ๊ฒฝ์์ ๋ค์ํ ์กฐ์ง๊ณผ ํ์ ํ ๊ฒฝํ
- ์ ๋ฌด ์ธ์ด๋ก์ ์์ด ์ฌ์ฉ์ ๋ํ ํธ์ํจ
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์ฐ๋ ์ฌํญ ๐
- ์ ๋์ ์ ๊ณต(STEM, ๊ธ์ต, ๊ฒฝ์ ํ, ํต๊ณ ๋ฑ) ํ์ฌ ํ์
- ๋ฐ์ดํฐ ๋ถ์, ๋ชจ๋ธ๋ง, ์คํ์ ์ํ Python ํ์ฉ ๊ฒฝํ
- ์์ธก, ์ต์ ํ, ๋๋ ์ ์ฉํ ๋จธ์ ๋ฌ๋ ๋ชจ๋ธ ๊ฒฝํ
- ์ด์ปค๋จธ์ค, ํธ๋ ๋๋ฆฌ๋ฒ๋ฆฌ, ๋ฌผ๋ฅ, ๋ง์ผํ๋ ์ด์ค ํ๋ซํผ ๊ฒฝํ
- Data Science, ๊ณ ๊ธ ์ ๋๋ฆฌํฑ์ค, AI ๊ธฐ๋ฐ ๋น์ฆ๋์ค ์ญํ ๋ก์ ์ฑ์ฅ์ ๋ํ ๊ด์ฌ
- ์์ฌ(MS) ๋๋ MBA ํ์ ๋ณด์ ์ ์ฐ๋
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Equal Opportunities for All
Coupang is an equal opportunity employer. Our unprecedented success could not be possible without the valuable inputs of our globally diverse team.
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About Eats Analytics Team ๐
The vision of the Eats Analytics Team is toย solve complex business problems through data, analytics, and applied AI, ensuring that every decision at Coupang Eats is both data-informed and impact-driven.
Our team goes beyond traditional reporting or operational support. We work closely with business, product, and operations leaders toย define problems, build analytical and data models, and operationalize insights at scale. Analytics at Coupang Eats spansย business strategy, experimentation, forecasting, and AI-driven decision making, providing team members with opportunities to grow toward Data Science, Machine Learning, or advanced Business Analytics roles.
As a Data Analyst, you will work end-to-endโfrom problem definition to model-driven insights to real-world operational executionโwhile gaining exposure to large-scale data, experimentation platforms, and AI-enabled business use cases.
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Responsibilities ๐
- Solve diverse business problems using data, analytics, and applied AIย across delivery operations, merchant ecosystem, customer growth, and marketplace dynamics
- Partner with business and product leaders toย translate ambiguous business questions into analytical frameworks and data models
- Design, execute, and analyzeย large-scale A/B tests and experiments, evaluating short-term impact and long-term business implications
- Develop and maintain analytical datasets, pipelines, and models (e.g., forecasting, optimization, segmentation) thatย support both operational and strategic decision-making
- Apply statistical analysis, modeling, and experimentation toย optimize core business metrics such as delivery time, cost efficiency, demand-supply balance, and customer retention
- Enable operational excellence byย operationalizing models and insights into daily decision workflows, while continuously improving methodologies
- Own key metrics and provideย forward-looking insightsย rather than purely retrospective reporting
- Conduct deep-dive analyses on customer, merchant, and operational data toย identify scalable growth opportunities
- Communicate findings and recommendations clearly to non-technical stakeholders, influencing decisions at multiple organizational levels
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Key Performance Indicators
- Business impact driven by analytics, experiments, and models
- Improvement in customer, merchant, and operational KPIs (retention, efficiency, unit economics)
- Adoption and effectiveness of analytical models and insights in daily operations
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Basic Qualifications ๐
- 5+ years of experience applying analytics, data analysis, or data science to solve business problems
- Strong SQL skills and experience with ETL, data modeling, and large-scale datasets
- Experience owning analytics for a business domain, product area, or operational function
- Strong analytical thinking with the ability to connect data insights to business outcomes
- Experience working in fast-paced, ambiguous environments with cross-functional stakeholders
- Comfortable using English as a working language
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Preferred Experience ๐
- Bachelorโs degree in a quantitative field (STEM, Finance, Economics, Statistics)
- Experience with Python for data analysis, modeling, or experimentation
- Exposure to forecasting, optimization, or applied machine learning models
- Background in e-commerce, food delivery, logistics, or marketplace platforms
- Interest in growing towardย Data Science, Advanced Analytics, or AI-driven business roles
- Advanced degree (MS or MBA) is a plus
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Recruitment Process and Others
Recruitment Process
- Application Review - SQL Live Coding Interview - Onsite (or Virtual Onsite) Interview โ 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.
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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 veteranโs benefits, the disabled, etc.) may receive preferential treatment for employment in accordance with applicable laws.
- 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.
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Privacy Notice
- Your personal information will be collected and managed by Coupang as stated in the Application Privacy Notice is located below.
https://privacy.coupang.com/en/land/jobs/
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Document Return Policy
- This notification is given pursuant to Article 11 (6) of the Fair Hiring Procedure Act.
- A job applicant, who has applied but not been finally selected for a position at Coupang (the โCompanyโ), 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.
- 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 โRequest for Return of Hiring Documentsโ [Annex Form No. 3 in the Enforcement Rule of the Fair Hiring Procedure Act] and submit It by email ([email protected]). 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 applicantโs designated address via registered mail. Please be informed that the job applicant is required to pay the postage on the registered mail.
- In preparation for a job applicantโs 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.
- The above paragraphs 1 - 4 shall only apply when the labor-related laws of Korea govern the application. They are otherwise not applicable.
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Equal Opportunities for All
- Coupang is an equal opportunity employer. Our unprecedented success could not be possible without the valuable inputs of our globally diverse team.
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