Sr~Staff Data Analyst (Coupang Eats)
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Eats Analytics ํ ์๊ฐ ๐ Eats Analytics ํ์ ๋น์ ์ ๋ฐ์ดํฐ, ๋ถ์, ๊ทธ๋ฆฌ๊ณ ์ ์ฉํ AI๋ฅผ ํตํด ๋ณต์กํ ๋น์ฆ๋์ค ๋ฌธ์ ๋ฅผ ํด๊ฒฐํจ์ผ๋ก์จ , Coupang Eats์ ๋ชจ๋ ์์ฌ๊ฒฐ์ ์ด ๋ฐ์ดํฐ์ ๊ธฐ๋ฐํ๊ณ ์ค์ง์ ์ธ ์ํฉํธ๋ฅผ ์ฐฝ์ถํ๋๋ก ๋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 ๋ถ์์ ๋น์ฆ๋์ค ์ ๋ต, ์คํ(Experimentation), ์์ธก(Forecasting), ๊ทธ๋ฆฌ๊ณ AI ๊ธฐ๋ฐ ์์ฌ๊ฒฐ์ ์ ๋ฐ์ ๊ฑธ์ณ ์์ผ๋ฉฐ, ํ์๋ค์ Data Science, Machine Learning, ํน์ ๊ณ ๊ธ ๋น์ฆ๋์ค ์ ๋๋ฆฌํฑ์ค ์ญํ ๋ก ์ฑ์ฅํ ์ ์๋ ๊ธฐํ๋ฅผ ์ป๊ฒ ๋ฉ๋๋ค. Data Analyst๋ก์ ๋น์ ์ ๋ฌธ์ ์ ์๋ถํฐ ๋ชจ๋ธ ๊ธฐ๋ฐ ์ธ์ฌ์ดํธ ๋์ถ, ์ค์ ์ด์ ์คํ๊น์ง ์๋ํฌ์๋๋ก ๊ด์ฌ ํ๊ฒ ๋๋ฉฐ, ๋๊ท๋ชจ ๋ฐ์ดํฐ, ์คํ ํ๋ซํผ, AI ๊ธฐ๋ฐ ๋น์ฆ๋์ค ํ์ฉ ์ฌ๋ก๋ฅผ ํญ๋๊ฒ ๊ฒฝํํ๊ฒ ๋ฉ๋๋ค. ์ฃผ์ ์ ๋ฌด ๐ ๋ฐฐ๋ฌ ์ด์, ๋จธ์ฒํธ ์ํ๊ณ, ๊ณ ๊ฐ ์ฑ์ฅ, ๋ง์ผํ๋ ์ด์ค ๊ตฌ์กฐ ์ ๋ฐ์ ๊ฑธ์ณ ๋ฐ์ดํฐ-๋ถ์-์ ์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, ์์-๊ณต๊ธ ๊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 ์๋ ๋ฏธ๋์งํฅ์ ์ธ์ฌ์ดํธ ์ ๊ณต ๊ณผ ํ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 ํต์ฌ ์ฑ๊ณผ ์งํ (KPI) ๋ถ์, ์คํ, ๋ชจ๋ธ์ ํตํด ์ฐฝ์ถ๋ ์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 ์๊ฒฉ ์๊ฑด ๐ ๋น์ฆ๋์ค ๋ฌธ์ ํด๊ฒฐ์ ์ํด ๋ฐ์ดํฐ ๋ถ์, ์ ๋๋ฆฌํฑ์ค, ๋๋ ๋ฐ์ดํฐ ์ฌ์ด์ธ์ค๋ฅผ ์ ์ฉํ 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 ์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 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. About Eats Analytics Team ๐ The vision of the Eats Analytics Team is to 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 to define problems, build analytical and data models, and operationalize insights at scale . Analytics at Coupang Eats spans 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-end-from problem definition to model-driven insights to real-world operational execution-while gaining exposure to large-scale data, experimentation platforms, and AI-enabled business use cases. Responsibilities ๐ Solve diverse business problems using data, analytics, and applied AI across delivery operations, merchant ecosystem, customer growth, and marketplace dynamics Partner with business and product leaders to translate ambiguous business questions into analytical frameworks and data models Design, execute, and analyze 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) that support both operational and strategic decision-making Apply statistical analysis, modeling, and experimentation to optimize core business metrics such as delivery time, cost efficiency, demand-supply balance, and customer retention Enable operational excellence by operationalizing models and insights into daily decision workflows , while continuously improving methodologies Own key metrics and provide forward-looking insights rather than purely retrospective reporting Conduct deep-dive analyses on customer, merchant, and operational data to identify scalable growth opportunities Communicate findings and recommendations clearly to non-technical stakeholders, influencing decisions at multiple organizational levels 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 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 Preferred Experience ๐ Bachelor's degree in a quantitative field (STEM, Finance,
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