Business Intelligence Engineer, SCOT - Automated Inventory Management

Amazon; London; On-site; GBP 50,000 - 70,000; Full time

Job summary

A leading company is seeking a Business Intelligence Engineer to enhance customer experience through data analytics and innovative solutions. This role involves analyzing complex datasets, collaborating with diverse teams, and presenting insights to senior management. Ideal candidates will have extensive experience in data analytics tools and a passion for problem-solving.

Qualifications

• 3+ years of data analysis experience with various tools.
• Experience in data visualization and modeling.

Responsibilities

• Analyze large data streams and present insights to management.
• Collaborate with Product Managers to improve customer experience.

Skills

Data Analytics

Statistical Analysis

Data Visualization

Data Modeling

ETL

SQL

Python

Tools

Redshift

Oracle

NoSQL

Tableau

Quicksight

R

SAS

Matlab

AWS

EC2

DynamoDB

S3

Job description

Business Intelligence Engineer, SCOT - Automated Inventory Management

Have you ever ordered a product on Amazon and when that box with the smile arrived, wondered how it got to you so fast? Wondered where it came from and how much it cost Amazon? If so, Amazon’s Supply Chain Optimization Technology (SCOT) organization is for you. At SCOT, we solve deep technical problems and build innovative solutions in a fast-paced environment working with smart & passionate team members. (Learn more about SCOT: http://bit.ly/amazon-scot)
Our vision is to ensure Amazon Customers have the best experience on Amazon, throughout the year, and do not have to compromise with a less than optimal experience during High traffic / Deal events.

SCOT Team is seeking highly motivated individuals with exceptional data analytics skills and a passion for tackling intricate challenges. In this role, you will utilize your expertise to inform impactful business decisions that enhance customer experience and contribute to long-term free cash flow growth. You will gain a comprehensive understanding of Amazon's systems and supply chain processes through collaboration with diverse teams across product, science, tech, retail categories, finance, and operations.

This role will require partnering closely with Product Managers across SCOT to segment our key Customer Experience and Supply Chain metrics, such as SoROOS and Local-In-Stock through the year, identify key opportunities to improve our system and process, to deliver Best-At-Amazon experiences for Customers throughout the year.

Key job responsibilities
• Analyze and synthesize large data streams across multiple systems/inputs.
• Work with Product Managers to understand customer behaviors, spot system defects, and benchmark our ability to serve our customers, improving a wide range of internal products that impact inventory availability for customers both nationally and regionally
• Develop business insights basis data extraction, data analytics, trend deduction & Pattern recognition.
• Present these business insights to senior management/executives.
• Create advanced dashboard to help a large group of teams to consume insights make changes to business process and track progress.
• Build analytical models that can help improve business outcomes at scale enhancing current system abilities.

BASIC QUALIFICATIONS

- 3+ years of analyzing and interpreting data with Redshift, Oracle, NoSQL etc. experience
- 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

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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Posted: May 15, 2025 (Updated about 16 hours ago)

Posted: May 13, 2025 (Updated about 19 hours ago)

Posted: May 15, 2025 (Updated about 19 hours ago)

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