亚马逊Business Analyst Intern (产品质量管理，深圳，2026实习)
任职要求
基本任职资格 - Speak, write, and read fluently in English - Speak, write, and read fluently in Mandarin - Graduate between Nov 2026 to Sept 2027, currently working towards a Bachelors (BS) or Masters (MS) in Engineering, Computer Science, Data Science, Business Analytics, Information Management, Mathematics or similar; - 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 优先任职资格 - Prior internship experience in business analytics, AI/ML projects, software development, or data engineering - Experience with AI agent frameworks, workflow a…
工作职责
• 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; • Support quality assurance processes/testings and contribute to continuous improvement initiatives.
- Conduct in-depth Product related data analysis to support business needs; - Support Product Quality team AI Agent use case studies and prototype development; - Build data pipelines and automation tools that integrate multiple data sources, enable real-time decision-making, and track key business metrics; - 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.
Scope of Work: 1. Update KPI metrics, monitor KPI performance and support the KPI performance deep dive by raw data sharing and simple analysis; 2. Provide data support for team operations, projects and ad-hoc requests; 3. Dive into data and identify improvement area, support data pipeline automation development; 4. Design, develop and maintain scaled, automated, dashboards that will support business needs Duration: At least 4 days per week, 4-6 months
1) Support performance report(weekly & monthly) 2) Support virtualization tool development and maintenance 3) Query optimization & consolidation 4) Documentation maintenance A day in the life 1) Reports preparations includes but not limit for collecting and formatting offline data/file. 2) virtualization tool Quicksight maintenance and development if any. 3) Query optimization for existing data pipeline 4) Documentation maintenance
1) Support performance report(weekly & monthly) 2) Support virtualization tool development and maintenance 3) Query optimization & consolidation 4) Documentation maintenance A day in the life A day in the life 1) Reports preparations includes but not limit for collecting and formatting offline data/file. 2) virtualization tool Quicksight maintenance and development if any. 3) Query optimization for existing data pipeline 4) Documentation maintenance