쿠팡은 고객이 쿠팡 앱을 열어보는 순간부터 상품을 문 앞으로 배송 받는 순간까지, 고객 한 분 한 분에게 감동을 줄 수 있도록 쇼핑의 경험을 새롭게 창조하고 있습니다. 뛰어난 엔드투엔드 이커머스와 물류 네트워크, 광적으로 고객에게 집중하는 문화를 바탕으로 쿠팡은 속도, 셀렉션, 가격에 있어 타협하지 않습니다. 현재 쿠팡은 신선 식품을 포함한 수백만 종류의 상품을 엄청나게 빠른 속도로 연중무휴 몇 시간 이내에 전국 배송하고 있습니다.
쿠팡은 세계에서 가장 크고 빠르게 성장하는 시장 중 하나인 한국의 수백만 소비자들을 위해 서비스를 제공하고 있습니다. 우리는 고객, 직원, 파트너들의 일상을 어떻게 혁신할 수 있을지 매 순간 고민합니다. 아직 아무도 풀지 못한 문제를 해결함으로써 사람들이 “쿠팡 없이 어떻게 살았을까?”라고 묻는 세상을 만들고자 합니다. 쿠팡은 서울뿐만 아니라 베이징, LA, 시애틀, 상하이와 실리콘밸리 등에 오피스를 두고 있는 글로벌 기업입니다.
Customer Experience (CX) Product Analytics 팀은 고객들의 이커머스 여정에서 모바일/웹 프로덕트와 상호 작용하는 방식을 개선하는 것을 목표로 합니다. 또한 데이터를 통합하여 실행 가능한 인사이트를 생성하고, 복잡한 비즈니스 문제에 해결책을 제시하며 쿠팡의 고객에 대한 깊은 이해를 가능하게 합니다.
· 서류전형 - 쿼리테스트 - 1차 화상면접 - 2차 화상면접 - 최종 합격
· 전형 절차는 직무별로 다르게 운영될 수 있으며, 일정 및 상황에 따라 변동될 수 있습니다.
· 전형 일정 및 결과는 지원서에 등록하신 이메일로 개별 안내드립니다.
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, “How did we ever live without Coupang?” Coupang is a global company with offices in Beijing, Los Angeles, Seattle, Seoul, Shanghai, and Silicon Valley.
We’re part of Customer Experience Product team, which aims to improve how our customers interact with your mobile/web products with their e-commerce journey.
We’re 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.
· 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.
· Validate hypotheses – generate test hypotheses, validate opportunities and recommend actions that can have positive improvements in customer experience and business KPIs.
· Test Analysis – Drive proper A/B analysis with statistical rigor and perform cohort studies to answer “why?” on test result drivers. Ideate more complex tests from an analytical and insightful reporting perspective.
· 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)
· 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
· 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
· Explore and test more technically/computationally efficient solutions. Know how to ingest, process, and analyze data.
· Improve dataset quality and automate manual processes
· Provides insights and solutions that inform product team's business decisions
· Communicate proposals, findings with stakeholders and document through wiki for further consumption and distribution
· For more senior roles, we expect you to be able to own an analytical domain of increasing complexity within the CX products and independently engage with multiple POs to prioritise and drive analytical/decision science agenda, while managing a small team(2-4) of analysts.
· 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.
· Understanding of A/B tests and its statistical concepts, including Bayesian statistics, with experience in designing and interpretation of A/B test results
· Having a comprehensive understanding of distributed systems, data modelling, and scientific methods. Highly proficient in descriptive statistics and inferential statistics
· Good presentation and communication skills in explaining data, as we often engage non-data savvy stakeholders
· 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
· Good command of English is a plus