Amazon.com Services LLC

Business Intelligence, Business Intel Engineer, operations

BusinessIntelEngineerII,SCOT

$100–160k Bellevue, Washington, United States FULL TIME
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Mid candidates.

The Brief

“Business Intel Engineer II, SCOT at Amazon.com Services LLC. Skills: Business Intelligence, Data Engineering, Analytics. Performing complex analysis to understand behavior of automated. Identify root cause of system / process issues”

What You'll Achieve.

Drive business improvements

Industry & Context.

Business Intelligence, Business Intel Engineer, operations
Problems you'll solve

Root cause analysis; Troubleshooting

What They're Looking For.

Must Have

Analyzing and interpreting data with Redshift, Oracle, NoSQL, Data visualization using Tableau, Quicksight, or similar tools, Data modeling, warehousing and building ETL pipelines, Statistical Analysis packages such as R, SAS and Matlab, SQL to pull data from a database or data warehouse, Scripting experience (Python) to process data for modeling, Experience in the dataI space, Bachelor's degree in engineering, statistics, computer science, mathematics, or a related quantitative field

Nice to Have

Experience with AWS solutions such as EC2, DynamoDB, S3, and Redshift, Data mining, ETL, etc. and using databases in a business environment with large-scale, complex datasets, Master's degree or above in a quantitative field

What You'll Do.

Performing complex analysis to understand behavior of automated

Identify root cause of system / process issues

Provide insight on potential solutions

Building audits to identify trend breaks or defects

Assessing end-to-end suite of audits

Identifying opportunities for enhancements and simplification

Creating new solutions to automate business process

Supporting improvement of automated audit workflow system

Integrating new audits

Providing input on future developments/roadmap

Developing dashboards and insight products

Fostering culture of continuous engineering improvement

How You'll Work.

Team & Collaboration

Collaborate with other teams; Work with others BIEs

Communication Scope

Present findings to senior audiences

Full Job Description

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 automated large-scale business operations, 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. Key job responsibilities - Performing complex analysis to understand the behavior of automated inventory management systems, identify the root cause of system / process issues and provide insight on pot

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