쿠팡은 세계에서 가장 빠르고 크게 성장하는 Ecommerce 기업 입니다. 우리는 고객, 직원, 파트너 그리고 우리를 둘러싼 모든 사람들의 일상을 어떻게 혁신 할 수 있을 지 매 순간 고민합니다. 우리는 아직 아무도 풀지 못한 문제를 해결함으로써 사람들이 이렇게 묻는 세상을 만들고자 합니다. “쿠팡 없이 어떻게 살았을까?” 쿠팡은 서울뿐만 아니라 베이징, LA, 시애틀, 상하이와 실리콘밸리 등에 오피스를 두고 있는 글로벌 기업입니다.
As our Sr Manager, Business Analysis for CRM Growth Marketing, you will be responsible for operational targeting and performance reporting to make our consumer experience world-class. With a span of ownership that includes the Retail Systems, Benefits and Promotions Platform systems, and CRM Platforms Systems, this leadership role is responsible for providing targeting and CRM insights allowing for data-driven decisions and performance assessments. This role will leverage existing Datawarehouse and retail time reporting capabilities and be able to build new tables as needed to support targeting for CRM team with and without promotions that will drive key customer actions to increase customer lifetime value and contribute to company’s growth
- Create analytics, insights, and reports that executives, CRM marketing team, and engineering leadership. will leverage to make investment decisions and as an input for requirements development and tools creation.
- Generate targeting list and actionable insights related to customer acquisition, cross sell and upsell to maximize customer lifetime value with and without promotions (discounts and coupons).
- Establish scalable, efficient, automated processes for large scale data analyses and drive analytics projects that leverage this data analysis.
- Over 10 years in total experiences with at least 7~8 years experiences in data analysis with expertise in SQL, SQL tuning, and relational database systems
- Experience using business intelligence reporting tools (Tableau, Data Cubes, Power BI, etc.)
- Knowledge of data management fundamentals and data storage principles
- Excellent verbal and written communication skills in both English and Korean
- Expertise in managing a team of Business Analyst
- Experience building/operating highly available, distributed systems of data extraction, ingestion, and processing of large data sets
- Experience using a programming language (R, SAS, Python, Java, etc.) for automation, job scheduling, and statistical analysis
- Knowledge of distributed systems as it pertains to data storage and computing
- Demonstrated strength in data modeling, ETL development, and data warehousing