Business Analyst Intern (Sourcing Team，深圳，2026实习)

Description du poste:

请注意，申请此实习岗位需要满足如下条件：
- 毕业时间：26年10月至27年9月之间毕业
- 实习时间：2026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' Global Sourcing Program team is looking for customer-obsessed interns to lead AI-driven automation initiatives that improve operational efficiency across the product lifecycle for our Private Brands business. The duration of the internship will be 24 weeks starting from March 2026. Interns will work in the Amazon office in Nanshan, Shenzhen.

The successful candidates will enjoy building AI agents, automation solutions, and data pipelines that streamline product development, supply chain operations, and post-launch performance optimization. The ideal candidates will thrive in a highly collaborative, analytical, creative, and fast-paced environment. The ideal candidates must be self-driven, have strong problem-solving skills to break down complex workflows, and a results-oriented mindset to deliver measurable business impact. Finally, candidates must also be strong communicators, with the ability to explain technical solutions to business stakeholders clearly and effectively.

Key job responsibilities
- Design and develop AI agents that automate workflows across product launch readiness, catalog quality management, supply chain visibility, and post-launch performance optimization
- Build data pipelines and automation tools that integrate multiple data sources, enable real-time decision-making, and track key business metrics
- Develop conversational AI assistant and detection systems that help business teams identify issues, prioritize actions, and improve operational efficiency at scale
- Collaborate with cross-functional teams including Sourcing, Quality, Marketing, Business Management, Technology to identify automation opportunities, define use cases, and measure business impact
- Continuously optimize existing automation solutions based on user feedback, operational metrics, and evolving business requirements

A day in the life
You'll start your day analyzing workflows and data to identify automation opportunities. You'll spend time building and testing AI agents using prompt engineering and coding tools, designing data pipelines, collaborating with business teams to refine requirements, and measuring the impact of your solutions on key metrics like launch readiness, operational efficiency, issue resolution speed, and time savings. You'll present findings to stakeholders and iterate on solutions based on feedback

Profil requis du candidat:

- Speak, write, and read fluently in English
- Speak, write, and read fluently in Mandarin
- Graduate between Oct 2026 to Sept 2027, currently working towards a Bachelors (BS) or Masters (MS) in Computer Science, Data Science, Business Analytics, Information Management, or related technical field
- Proficient in SQL for data querying, analysis, and manipulation across large datasets
- Knowledge of Python and experience using AI coding assistants (e.g., Claude Code, Cursor, Cline, GitHub Copilot, Q) to generate, understand, and debug code
- Strong prompt engineering skills with experience using LLM tools (ChatGPT, Claude, or similar)
- High attention to detail, comfortable with "hands-on" task management, and proven ability to manage multiple competing priorities
- Work 4 to 5 days per week for at least 6 months, physically in Shenzhen
- Prior internship experience in business analytics, AI/ML projects, software development, or data engineering
- Experience with AI agent frameworks, workflow automation tools, or MCP (Model Context Protocol)
- Familiarity with AWS services (Bedrock, S3, Lambda, Redshift, Glue)
- Experience with data visualization and dashboard development (e.g., QuickSight, Tableau)
- Product management mindset: ability to define use cases, gather requirements from stakeholders, establish success metrics, and measure ROI
- Knowledge of eCommerce operations, supply chain processes, catalog management, or product development workflows
- Understanding of data pipeline concepts: ETL/ELT, data quality checks, incremental refresh, monitoring/alerting

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you're applying in isn't listed, please contact your Recruiting Partner