Business Intelligence Engineer, SCOT Automated Inventory Management

The Supply Chain Optimization Technologies (SCOT) organization owns Amazon’s global inventory management systems: we decide what, when, where, and how much we should buy to meet Amazon’s business goals and to make our customers happy. We do this for millions of items, for hundreds of product lines worth billions of dollars of inventory world-wide. Our systems are built entirely in-house, and are on the cutting edge in automated large-scale business, inventory and supply chain planning and optimization systems. We foster new game-changing ideas, creating ever more intelligent and self-learning systems to maximize the efficiency of Amazon's inventory investment and placement decisions.

The Automated Inventory Management team within SCOT seeks an experienced and motivated Business Intelligence Engineer to develop analytical models and tools to automate the auditing of the SCOT systems. Such tools may include algorithms, metric bridges, dashboards, processes and workflow systems.

The successful candidate will have strong quantitative data mining and modeling skills and be comfortable working on new and sometimes ambiguous problems from concept through to execution. They will have strong communication and leadership skills, will be able to collaborate with other teams (e.g. software development, business owners, product managers) and to present findings to senior audiences to drive business improvements. As well we expect this candidate to raise the bar on any of the following categories: Data Warehousing, Data Architecture, Performant Self Service Toolsets and Data analytics. Candidate might be willing to work with the others BIEs in order to solve organizational problems at scale and setting the grounds of a healthy data products offer while delivering what is required by business.

• Responsibilities may include: - Performing complex analysis to understand the behavior of automated inventory management systems, identify the root cause of system / process issues and provide insight on potential solutions.
• - Building audits (analytical products) to identify trend breaks or defects at scale for millions of products and multiple Marketplaces globally
• - Assessing the end-to-end suite of audits and identifying opportunities for enhancements and simplification, working with other audit owners
• - Creating new solutions to automate the business process of identifying and resolving defects (e.g. through metric dashboards and automated alarms, self service dashboard, Single source of truth tables... )
• - Supporting the improvement of the automated audit workflow system: integrating new audits and providing input on the future developments/roadmap
• - Developing dashboards and insight products
• - Fostering culture of continuous engineering improvement through blueprints, mentoring, feedback, and metrics

Basic qualifications

• - Experience in analyzing and interpreting data with Redshift, Oracle, NoSQL etc.
• - Experience with data visualization using Tableau, Quicksight, or similar tools
• - Experience with data modeling, warehousing and building ETL pipelines
• - Experience in Statistical Analysis packages such as R, SAS and Matlab
• - Experience using SQL to pull data from a database or data warehouse and scripting experience (Python) to process data for modeling
• - Experience with SQL
• - Experience in the data/BI space

Preferred qualifications

• - Experience with AWS solutions such as EC2, DynamoDB, S3, and Redshift
• - Experience in data mining, ETL, etc. and using databases in a business environment with large-scale, complex datasets

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