About the Team ๐
Customer Experience (CX) Product Analytics ํ์ ๊ณ ๊ฐ๋ค์ ์ด์ปค๋จธ์ค ์ฌ์ ์์ ๋ชจ๋ฐ์ผ/์น ํ๋ก๋ํธ์ ์ํธ ์์ฉํ๋ ๋ฐฉ์์ ๊ฐ์ ํ๋ ๊ฒ์ ๋ชฉํ๋ก ํฉ๋๋ค. ๋ํ ๋ฐ์ดํฐ๋ฅผ ํตํฉํ์ฌ ์คํ ๊ฐ๋ฅํ ์ธ์ฌ์ดํธ๋ฅผ ์์ฑํ๊ณ , ๋ณต์กํ ๋น์ฆ๋์ค ๋ฌธ์ ์ ํด๊ฒฐ์ฑ ์ ์ ์ํ๋ฉฐ ์ฟ ํก์ ๊ณ ๊ฐ์ ๋ํ ๊น์ ์ดํด๋ฅผ ๊ฐ๋ฅํ๊ฒ ํฉ๋๋ค.
Responsibilities ๐
ยท Product ์ ๋ต ๊ฐ๋ฐ/์ง์์ ์ํ ์ ๋์ ๋ถ์, ์คํ ๋ฐ ๋ฐ์ดํฐ ์ ์๋ฅผ ํตํด ๊ธฐ์ ์ ์ ๋ฌธ์ฑ์ ์ ์ฉํ๋ ๋์์, Product ๊ฐ์ ์ ์ํ ๊ธฐ๋์ ์๋จ์ ์ ์, ์ดํด, ํ ์คํธํ๊ณ ํต์ฐฐ๋ ฅ์ ๊ธฐ๋ฐํ ์ถ๊ฐ์ ์ธ ์ ์์ ํตํด ๋ก๋๋งต์ ์ถ์งํฉ๋๋ค.
ยท ๊ฐ์ค๊ฒ์ฆ - ํ ์คํธ ๊ฐ์ค์ ์ธ์ฐ๊ณ , ๊ธฐํ๋ฅผ ๊ฒ์ฆํ๊ณ ๊ณ ๊ฐ ๊ฒฝํ๊ณผ ๋น์ฆ๋์ค KPI์ ๊ธ์ ์ ์ธ ๊ฐ์ ์ ๊ฐ์ ธ๋ค ์ค ์ ์๋ ์กฐ์น๋ค์ ์ ์ํฉ๋๋ค.
ยท ํ ์คํธ ๋ถ์ - ํต๊ณํ์ ์ผ๋ก ์ ํํ๊ณ ์ ํฉํ A/B analysis ์ ๋ฆฌ๋ฉํ๊ณ , ํ ์คํธ ๊ฒฐ๊ณผ๋ฅผ ์ด๋์ด๋ด๋ ์์ธ์ ๋ํ โWHYโ์ ๋ตํ๊ธฐ ์ํด ์ฝํธํธ ์ฐ๊ตฌ๋ฅผ ์งํํฉ๋๋ค. ๋ถ์์ ์ด๊ณ ํต์ฐฐ๋ ฅ ์๋ Report ๊ด์ ์์ ์ข ๋ ๋ณต์กํ Test๋ฅผ ๊ณ ์ํฉ๋๋ค.
ยท ์ฃผ์ Data Artifacts ์ Lineage (ex: ETL, ๋ฐ์ดํฐ ๋ชจ๋ธ, ์ฟผ๋ฆฌ) ๋ฅผ ์ ์งํ๋ฉฐ, ์งํ์ค์ธ ํ ์คํธ ์ฑ๋ฅ/๊ฒฐ๊ณผ ๋ชจ๋ํฐ๋ง์ ์ํด ์๋ํ๋ ๋ฐ์ดํฐ ์ํฌํ๋ก์ฐ์ ๋์๋ณด๋๋ฅผ ๊ฐ๋ฐํฉ๋๋ค.
ยท ๊ด๋ จ ์๊ฐํ ํด (Tableau/PowerBI/Superset ๋ฑ) ์ ํ์ฉํ์ฌ Metrics์ ํธ๋ํนํ๊ณ , ์ด์ ๋ฐ์ดํฐ๋ฅผ ์กฐ์ฌํ๋ฉฐ, ์ ์ ํ ์ฐจ์์์ ์งํ๋ฅผ ์ถ๊ฐ์ ์ผ๋ก ๋ถ๋ฅํ์ฌ ์ฌ์ธต์ ์ธ dynamics์ ๋ฐํ๋ ๋๋ค.
ยท ๋น์ฆ๋์ค์ ๊ธฐ์ ์ ๋ฐ ์ด์์ ์ธ ๋ฉด์์์ ์ธ๋ถ ์กฐ๊ฑด์ฌํญ(ex: key dependencies, business drivers/KPIs, develop actionable business insights ๋ฑ)๋ค์ ๋ฉด๋ฐํ ํ์ํด์ ๊ฑด์ค์ ์ธ ๊ธฐ์ ์ ๋ ผ์ ๋ฐ ๊ฒ์ฆ์ ๊ธฐ์ฌํฉ๋๋ค.
ยท ๊ธฐ์ ์ /์์คํ ์ ์ผ๋ก ๋ ํจ์จ์ ์ธ ์๋ฃจ์ ์ ์์๋ณด๊ณ ํ ์คํธํฉ๋๋ค. ๋ฐ์ดํฐ๋ฅผ ์ด๋ป๊ฒ ์ํ, ์ฒ๋ฆฌ, ๋ถ์ํ๋์ง ์ดํดํฉ๋๋ค.
ยท ๋ฐ์ดํฐ์ ํ๋ฆฌํฐ๋ฅผ ๊ฐ์ ํ๊ณ ๋งค๋ด์ผ ํ๋ก์ธ์ค๋ฅผ ์๋ํํฉ๋๋ค.
ยท ํ๋ก๋ํธ ํ์ ๋น์ฆ๋์ค ๊ฒฐ์ ์ ์ํฅ์ ๋ฏธ์น๋ ์ธ์ฌ์ดํธ์ ์๋ฃจ์ ์ ์ ๊ณตํฉ๋๋ค.
ยท ์ดํด๊ด๊ณ์๋ค๊ณผ ์ ์๊ณผ ๋ฐ๊ฒฌ์ ์ ๋ํด ์ปค๋ฎค๋์ผ์ด์ ํ๊ณ ์ถํ ์ฌ์ฉ๊ณผ ๋ฐฐํฌ๋ฅผ ์ํด ์ํค๋ก ๋ฌธ์ํํฉ๋๋ค.
ยท ์ง๋ฌด์ Seniority์ ๋ฐ๋ผ CX ํ๋ก๋ํธ ๋ด์ ๋ณต์ก์ฑ์ด ๋์ ๋ถ์์ ์์ญ์ ๋ด๋นํ๊ฒ ๋๊ณ , ์ฌ๋ฌ PM๋ค๊ณผ ์ํธ์ ์ผ๋ก ์ ๋ฌดํ๋ฉฐ ํ๋ฌ๋ํธ ๋ถ์๋ฐ ๋น์ง๋์ค์ ์ฐ์ ์์ ๊ฒฐ์ ์ ์ค์ํ ์ํฅ๋ ฅ์ ๋ฐํ ํ ์ ์์ต๋๋ค.
Basic Qualifications ๐
ยท Querying Language (ex. SQL) ์ ์คํฌ๋ฆฝํธ ์ธ์ด (ํ์ด์ฌ) ์ฌ์ฉ ๊ฒฝํ.
ยท Spark์ ๋ํ ์ดํด๋๋ฅผ ๋ณด์ ํ์ ๋ถ, GPU (ex. RapidsAI CUDA) ์ฌ์ฉ ๊ฒฝํ (์ฐ๋ ์ฌํญ)
ยท ์ ๋๋ถ์ผ์ ํ์ฌ (STEM, Finance, Economics, Statistics)
ยท Data Analyst, Data Scientist ๋ฑ ๋ฐ์ดํฐ ๋ถ์ ๊ธฐ์ ์ ํ์๋กํ๋ ์ ๋ฌด ์ฝ 3๋ ์ด์์ ๊ฒฝํ
ยท A/B ํ ์คํธ์ Bayesian statistics์ ํฌํจํ A/B ํ ์คํธ์ ํต๊ณ ๊ฐ๋ ์ ๋ํ ์ดํด๋์, A/B ํ ์คํธ ์ค๊ณ, ๊ฒฐ๊ณผ ํด์ ๊ฒฝํ
ยท ๋ถ์ฐ ์์คํ , ๋ฐ์ดํฐ ๋ชจ๋ธ๋ง, scientific methods ์ ๋ํ ์ข ํฉ์ ์ธ ์ดํด๊ฐ ์๊ณ , ๊ธฐ์ ํต๊ณ/์ถ๋ฆฌ ํต๊ณ์ ๋ํ ๋์ ์ ๋ฌธ์ฑ์ ๋ณด์ .
ยท ๋ค์ํ stakeholders์ ๋์์ผ๋ก ๋ค์์ ํ๋ ์ ํ ์ด์ ์ ์งํํด๋ณธ ๊ฒฝํ ๋ฐ ํจ์จ์ ์ธ ์ปค๋ฎค๋์ผ์ด์ ์คํฌ์ ๋ณด์ .
ยท ์ ๋ฌด์ ์ฐ์ ์์๋ฅผ ํจ์จ์ ์ผ๋ก ์ ํ๊ณ , ๋น ๋ฅด๊ณ ์ญ๋์ ์ธ ํ๊ฒฝ์์ ํจ๊ณผ์ ์ธ ๊ฒฐ๊ณผ๋ฅผ ๋ฌ์ฑํ ์ ์๋ ์ญ๋ (๋ฉํฐํ ์คํน ์ญ๋)
Preferred Experience ๐
ยท ๊ณตํ ๋ฐ ๋น์ง๋์ค ํ์ (์/๋ฐ์ฌ or MBA)
ยท ํต๊ณ ๋ถ์์ ์ํ R/SAS ํ์ฉ ์ญ๋
ยท Hive, Presto, Airflow
ยท ๋ฐ์ดํฐ ์๊ฐํ (์: Tableau, Qlik, Looker, Power BI)
ยท ์์ฐ์ด (NLP) ์ฒ๋ฆฌ ๊ฒฝ๋ ฅ ์ฐ๋
ยท ์์ด ๋ฅํต์ ์ฐ๋
์ ํ ์ ์ฐจ ๋ฐ ์๋ด ์ฌํญ
์ ํ์ ์ฐจ: ์๋ฅ์ ํ - ๊ณผ์ ์ฝ๋ฉ ํ ์คํธ - ์ ํ๋ฉด์ - ๋น๋๋ฉด ํ์๋ฉด์ โ์ต์ข ํฉ๊ฒฉ
์ ํ์ ์ฐจ๋ ์ง๋ฌด๋ณ๋ก ๋ค๋ฅด๊ฒ ์ด์๋ ์ ์์ผ๋ฉฐ, ์ผ์ ๋ฐ ์ํฉ์ ๋ฐ๋ผ ๋ณ๋๋ ์ ์์ต๋๋ค.์ ํ์ผ์ ๋ฐ ๊ฒฐ๊ณผ๋ ์ง์์์ ๋ฑ๋กํ์ ์ด๋ฉ์ผ๋ก ๊ฐ๋ณ ์๋ด ๋๋ฆฝ๋๋ค.
์ฐธ๊ณ ์ฌํญ ๋ณธ ๊ณต๊ณ ๋ ๋ชจ์ง ์๋ฃ ์ ์กฐ๊ธฐ๋ง๊ฐ๋ ์ ์์ต๋๋ค.์ง์์ ๋ด์ฉ ์ค ํ์์ฌ์ค์ด ์๋ ๊ฒฝ์ฐ์๋ ํฉ๊ฒฉ์ด ์ทจ์๋ ์ ์์ต๋๋ค.๋ณดํ๋์์ ๋ฐ ์ฅ์ ์ธ ์ฌ๋ถ๋ ์ฑ์ฉ ๊ณผ์ ์์ ์ด๋ ํ ๋ถ์ด์ต๋ ๋ฏธ์น์ง ์์ต๋๋ค.
Sr./Staff Data Scientist_Customer Experience Product Analytics and Decision Science / Location: Seoul, Korea
Customer Experience Product Analytics and Decision Science (CX PA & DS) / Seoul, Korea
Coupang is one of the largest and fastest growing e-commerce platforms on the planet. We are on a mission to revolutionize everyday lives for our customers, employees and partners. We solve problems no one has solved before to create a world where people ask, โHow did we ever live without Coupang?โ Coupang is a global company with offices in Beijing, Los Angeles, Seattle, Seoul, Shanghai, and Silicon Valley.
About us :
Weโre part of Customer Experience Product team, which aims to improve how our customers interact with your mobile/web products with their e-commerce journey.
Weโre responsible for providing support in utilising decision science techniques in product development, along with discovery of customer behaviours within our products, in journey of creating better customer-facing products.
Qualifications :
ยท Wealth of experience in using querying language(e.g. SQL) and scripting language (Python) with understanding of Spark, experiencing of utilising GPU(e.g. RapidsAI, CUDA) for is a plus.
ยท Understanding of A/B tests and its statistical concepts, including Bayesian statistics, with experience in designing and interpretation of A/B test results
ยท Having a comprehensive understanding of distributed systems, data modelling, and scientific methods. Highly proficient in descriptive statistics and inferential statistics
ยท Good presentation and communication skills in explaining data, as we often engage non-data savvy stakeholders
ยท Having inquisitive mindset- should be ready to dive into the unknown, discover, and share findings with others, while employing critical thinking and detail-oriented focus to solve ambiguous and unstructured problems
ยท Good command of English is a plus
What you will do with us :
ยท Apply technical expertise with quantitative analysis, experimentation, and the presentation of data to aid the development of strategies for our products, while define, understand, and test opportunities and levers to improve the product, and drive roadmaps through your insights and recommendations.
ยท Validate hypotheses โ generate test hypotheses, validate opportunities and recommend actions that can have positive improvements in customer experience and business KPIs.
ยท Test Analysis โ Drive proper A/B analysis with statistical rigor and perform cohort studies to answer โwhy?โ on test result drivers. Ideate more complex tests from an analytical and insightful reporting perspective.
ยท Develop automated data workflows and dashboards to monitor ongoing test performance/results, with maintaining key data artifacts and lineage (e.g., ETL, data models, queries)
ยท Utilizes relevant visualization tools (Tableau/PowerBI/Superset/etc) to help track metrics and investigate data anomalies, and further segment metrics along suitable dimensions to reveal deeper dynamics
ยท Dive deeply into technical and operational details of the business (e.g., key dependencies, business drivers/KPIs, develop actionable business insights, etc.) and contribute to constructive technical discussions
ยท Explore and test more technically/computationally efficient solutions. Know how to ingest, process, and analyze data.
ยท Improve dataset quality and automate manual processes
ยท Provides insights and solutions that inform product team's business decisions
ยท Communicate proposals, findings with stakeholders and document through wiki for further consumption and distribution
Recruitment Process and Others
- Recruitment Process
- Application Review - Home Coding Test - Phone Interview - 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.
0 applies
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