Senior Data Analyst I

at  SHEIN

ABOUT US

SHEIN is a global online fashion and lifestyle retailer, offering SHEIN branded apparel and products from a global network of vendors, all at affordable prices. Headquartered in Singapore, SHEIN remains committed to making the beauty of fashion accessible to all, promoting its industry-leading, on-demand production methodology, for a smarter, future-ready industry.
Join our growth story!
Are you looking for an exciting new move in your career? SHEIN (www.sheingroup.com) is an international online fashion retailer that’s in an exciting new phase of our continued growth!
If you like to work fast, collaboratively and understand the true value of idea generation with a ‘customer first’ mentality - you’re on your way to being a right fit for us.
As a fast growing business with an immediate need to innovatively build out our talent infrastructure, we’re looking for a dynamic professional who is keen to work in an agile and evolving business environment. There’s work, and then there’s the work you’re passionate about.
The kind of work that’s an extension of who you are. That’s the work we do at SHEIN.
Our values consist of putting the customer first, going all out, acting and adapting, continuous learning & innovating and encouraging synergy & collaboration at all levels within the business.
If you feel like you belong, consider the job description below and apply.
Come shine at SHEIN and join our growth story!
We are currently seeking an experienced Senior Data Analyst I to join our team in Germany. As Senior Data Analyst I you will develop and manage a regional warehousing and logistics data monitoring system, oversee operational performance, and track KPI implementation across business departments with regular reporting and data visualization tasks.

Key Duties:

• Establish a regional warehousing and logistics data monitoring system, including maintaining underlying data, building data dashboards, regularly generating data reports, and other data visualization work;
• Monitor the overall operational health of warehousing and logistics, and periodically report any abnormalities;
• Follow up on the implementation of KPI in the business departments, predict and compare the actual situation.

SKILLS & QUALIFICATIONS:

1. Bachelor degree or above; 3+ years experiences in fulfillment business data analysis.
2. Data planning capability:
   Deeply understand the data status and business direction of the business line, output key plans, and formulate corresponding key actions.
3. Basic data construction capability:
   Deeply understand the relationship between buried points, indicators, and reports, abstract and analyze complex businesses, and build corresponding data foundations;
   According to the needs of business development, improve the data system of business lines, and use this system to timely discover problem points;
   Establish a framework and process for troubleshooting data anomalies to improve troubleshooting efficiency.
4. Business insight capability:
   Analyze and gain insights into different business modules of the responsible business line;
   Understand business line planning, proactively analyze opportunity points, and output data analysis conclusions and recommendations that affect business line decisions through efficient and comprehensive analysis.
5. Basic technical skills:
   Proficient in SQL code logic such as Hive and Presto, and proficient in data report design and development;
   Proficient in data visualization, such as Excel and Tableau;
   Proficient in the basic principles of buried points and ab experiments, and proficient in their application;
   Proficient in SPSS, R, Python (any one), with relevant project experience

• Establish a regional warehousing and logistics data monitoring system, including maintaining underlying data, building data dashboards, regularly generating data reports, and other data visualization work;
• Monitor the overall operational health of warehousing and logistics, and periodically report any abnormalities;
• Follow up on the implementation of KPI in the business departments, predict and compare the actual situation