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


· Advanced to expert knowledge of SQL
· 5+ years’ experience of quantitative experience in Business Intelligence or Data Science
· Bachelor's Degree in Computer Science, Information Management, Industrial Engineering, Mathematics, Statistics, Operations Research or Finance
· Experience processing large scale datasets, analyzing data to solve business problems and presenting impactful insights
· Advanced knowledge of data visualization tools (e.g. Tableau)
· Strong written and verbal communication skills. The role requires effective communication with colleagues from machine learning, economics and business backgrounds


· Master’s degree or higher in Computer Science, Information Management, Industrial Engineering, Mathematics, Statistics, Operations Research, or other technical field from an accredited university
· Domain knowledge in Buying, Logistics/Supply Chain, Transportation, Engineering
· Experience working in a fast-paced, high tech environment (preferably tech industry)
· Experience working in or with a complex international supply chain management organization
· Experience incubating and commercializing new ideas, working with product managers, research scientists and technical teams from concept generation through implementation
· Experience with statistical analysis, regression modeling and forecasting, time series analysis, data mining, financial analysis, and demand modeling (using statistical software such as scipy, scikit-learn or R)
· Experience using Python for scripting or statistical analysis
· Advanced to expert user of Microsoft Excel
· Experience with Redshift, Tableau, Quicksight, AWS (S3, EMR), SQL Spark, Python
· Passion for table tenis, padel or soccer

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