请注意，申请此实习岗位需要满足如下条件：

毕业时间：25年10月至26年9月之间毕业
实习时间：2025年开始，一周实习4-5天，持续6个月
工作地点：深圳市南山区
简历要求：请提供中英双语简历（放在一个文件中）

投递须知：
1 填写简历申请时，请把必填和非必填项都填写完整。提交简历之后就无法修改了哦！
2 学校的英文全称请准确填写。

Amazon Private Brands aims to offer customers a wide selection of low-priced products with good quality. HPB sourcing team strives to deliver value products by selecting the best-in-class suppliers, track and improve supplier performance, and protect customer by proactive defect avoidance. We are looking for customer-obsessed interns to lead initiatives that further develop workflow automation, improve datamining and visualization. Internship will locate in Nanshan, Shenzhen.

The successful candidate will enjoy diving deep into data and identifying insights, as well as have a curious mind on manufacturing and continuous improvement. The ideal candidate will thrive in a highly collaborative, analytical, creative, and fast-paced international environment. The ideal candidate must be self-driven and have the analytical horsepower to break down complex problems, and a strong will to get things done and deliver results. Finally, the candidate must also be a strong communicator, with the ability to communicate concisely and effectively.

What will you gain:
- Gain manufacturing industry and factory management knowledge;
- Apply your learnings in business environment, sharpening analytical and coding skills;
- Gain experience in a fast-paced, entrepreneurial working environment;
- Work with a diverse team with professionals from over 10+ different countries and various industries;
- Boost you resume with real world experience.

Deliverables
- Conduct in-depth Product related data analysis to support business needs;
- Design and implement data models based on excel templates, defining objects and attributes;
- Support Quality LLM use case studies;
- Upgrade lab testing dashboard by writing custom SQL and scripting to calculate additional attribute values and improve data visualization.


Key job responsibilities
- Learn Amazon Data infrastructure and tools, extract and integrate data from Datawarehouse for holistic analysis;
- Work with cross function stakeholders, provide data supports, business updates and solutions.

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