Sr. Business Intelligence Engineer , CNGS NBS (new Business & New Seller) Amazon Business

Sr. Business Intelligence Engineer

Are you passionate about leveraging data analytics and quantitative analysis skills to drive worldwide business impact? Are you excited about developing innovative solutions that help sellers succeed while optimizing Amazon's global operations? If so, this role could be perfect for you. The CN GS NBS ASE team is responsible for recruiting, driving growth and development of sellers in the Chinese market. Partnering with business, product, and engineering teams, we catalyze seller growth with comprehensive data analysis leveraging AI and data skills, to deliver unique insights, and actionable recommendations. We're seeking a Sr. Business Intelligence Engineer with rich experience on both technical and technical program management skill and to join our dynamic team focused on seller intelligence, analytics and operational optimization. This role combines strategic analytics capabilities with practical business applications to drive seller growth and operational excellence across Amazon's global markets.

Key job responsibilities:

• Translating business questions and concerns into specific analytical questions that can be answered with available data using BI tools; produce the required data when it is not available.
• Apply Statistical and Machine Learning methods to specific business problems and data.
• Create global standard metrics across regions and perform benchmark analysis.
• Ensure data quality throughout all stages of acquisition and processing, including such areas as data sourcing/collection, ground truth generation, normalization, transformation, cross-lingual alignment/mapping, etc.
• Communicate proposals and results in a clear manner backed by data and coupled with actionable conclusions to drive business decisions.
• Collaborate with colleagues from multidisciplinary science, engineering and business backgrounds.
• Develop efficient data querying and modeling infrastructure.
• Manage your own process. Prioritize and execute on high impact projects, triage external requests, and ensure to deliver projects in time.
• Utilizing code (SQL, Python, R, etc.) for analyzing data and building statistical models.