Description de l'offre
Are you interested in innovating to deliver a world-class level of service to Amazon's selling partners? The Selling Partner Paid Services (SPPS) team seeks to improve the customer experience on Amazon.com by working directly with selling partners on Amazon to improve value, selection and convenience across their business. Our team will invent and innovate across technology, processes and people to grow the program, improve seller engagement and satisfaction and enable scalable global solutions.
The Paid Services Analytics team is looking for a passionate analyst in the business intelligence space who will work closely with global stakeholders to identify the largest areas of opportunity for standardized self-service reporting. The ideal candidate is able to maintain a high standard of data quality and excellence in the work delivered but also to surprise and delight stakeholders by suggesting innovative ways to combine related elements of disparate reports. Success will come from the ability to educate and influence teams utilizing your reports in the various needs they serve and streamlining ad-hoc reporting in the paid services space.
The role's key responsibilities will include:
· Lead weekly reviews of ad hoc reporting requests to identify largest areas of opportunities
· Interact with SMEs across Amazon and company-wide tools to identify single sources of truth for data pertinent to our selling partners
· Consolidate end user requirements and create easy-to-use dashboards to be used by 100s of associates world-wide
· Lead launch notifications and training for dashboards you create
· Develop adoption mechanisms to track usage and receive/incorporate user feedback
· Bachelor's degree required (majors in Business, Engineering, Statistics, Computer Science, Mathematics or related field strongly preferred)
· 2+ years of relevant experience in data analysis, report building, research or similar work
· Experience with SQL and Excel
· Experience supporting small to medium sized projects involving complex data sets and high variability
· Experience consolidating large data sets into actionable, digestible reporting