Shipping & Delivery Support Quality Analyst, Sds Operations Excellence Program Team

Amazon's expanding Logistics products and services (e.g. Amazon Shipping, Flex, AMXL, and Amazon Global Logistics [AGL]) are creating new customer segments, including drivers, recipients, property managers, and global shippers. Shipping & Delivery Support (SDS) is a customer service organization dedicated to building world-class support for Amazon's transportation products and services across all customer segments.
SDS is looking for an energetic, curious, and customer obsessed Quality Analyst to help optimize the global Driver and Recipient support experiences. We are looking for a creative thinker with deep analytics experience who knows how to execute and deliver from concept. Ability and enthusiasm to be a leader on a team operating in a highly ambiguous environment is required.
The ideal candidate will have a rock-solid background in data analysis, including experience extracting and manipulating data using SQL, leveraging advanced Excel features for data analysis, and producing digestible business intelligence and actionable information. The candidate should also have strong communication and project management skills, enabling them to work with key business stakeholders to understand requirements and shape analytical deliverables. They should also have a demonstrated ability to think analytically about business, product, and technical challenges, with the ability to work cross-organizationally. A keen sense of ownership, drive, and scrappiness is a must.
Key job responsibilities

• Continuously advocate for customers
• Work with international cross-functional teams
• Design and execute analytic projects in collaboration with business, product, data engineering, finance, business analysts, and other specialists.
• Build data visualization reports and tools for self-service consumption of data, e.g., Tableau, QuickSight, and custom solutions.
• Analyze and extract relevant information from large amounts of both structured and unstructured data to help automate and optimize key processes, providing reliable insights.
• Partner with data engineering teams to improve data assets, quality, metrics and insights.
• Proactively identify opportunity areas for deep dive investigations and future program development.
• Write concise documents communicating results to stakeholders and visualize data to drive decision-making.