Business Intelligence Engineer

Job description

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 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 Fulfillment Insights team is focused on using cutting edge science to improve customer outcomes and transform our logistics, along with machine learning, and scalable distributed software in the cloud that automates and optimizes shipments to customers under the uncertainty of demand, pricing and supply. When customers place orders, our systems use real time, large scale optimization techniques to optimally choose from where to ship and how to consolidate multiple orders so that customers get their shipments on time or faster with the lowest possible transportation costs. One of our core responsibilities is to leverage big data to identify key patterns of success and failure, identify the areas we need to focus on first, understand root cause(s) that triggered failure, and to build predictive models that will help fix the most impactful problems. The amount of data, the variables that come into play, and diversity of customers and locations make this role very challenging and also fun. It's great for those who love solving problems, especially when dealing with a lot of ambiguity and asking lots of smart questions that will lead to the discovery of universal concepts, and truly innovative ML solutions that continuously improve the customer delivery experience.

As a Business Intelligence Engineer on Fulfillment Insights, you will:
· Directly interface with business customers, gathering requirements and delivering complete BI solutions.
· Analyze and extract relevant information from large amounts of data to help automate and optimize solutions to key business problems.
· Conceptualize models and solutions essential to delivering customer value.
· Work closely with research science, data & software engineering teams to build model implementations and integrate successful models and algorithms in production systems at very large scale.
· Recognize and adopt best practices in reporting and analysis: data integrity, test design, analysis, validation, and documentation
· Establish scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementation.
To help describe some of our challenges, we created a short video about Supply Chain Optimization at Amazon - http://bit.ly/amazon-scot

Amazon is an Equal Opportunity-Affirmative Action Employer – Minority / Female / Disability / Veteran / Gender Identity / Sexual Orientation / Age.

PREFERRED QUALIFICATIONS

· Master’s degree or higher in Computer Science, Information Management, Industrial Engineering, Maths, Statistics, Finance, or other technical field from an accredited university
· Domain knowledge in Buying, Logistics/Supply Chain, Transportation, Engineering
· Advanced knowledge of Oracle BI tools, MySQL, Linux/UNIX
· Experience with AWS solutions such as EC2, DynamoDB, S3, and Redshift
· Experience with statistical analysis, regression modeling and forecasting, time series analysis, data mining, financial analysis, and demand modeling
· Experience using Python for scripting or statistical analysis

Desired profile

BASIC QUALIFICATIONS

· Bachelor's Degree in Computer Science, Information Management, Industrial Engineering, Maths, Statistics, Finance, or related industry experience
· 2+ years of quantitative and qualitative experience in Business Intelligence or Data Science
· Experience processing large scale datasets, analyzing data to solve business problems and presenting impactful insights to business teams
· Advanced knowledge in SQL
· Knowledge and direct experience using business intelligence reporting/visualization tools (OBIEE, Business Objects, Cognos, Tableau, MicroStrategy, SSAS Cubes, etc.)
· Strong written and verbal communication skills. The role requires effective communication with colleagues from machine learning, economics and business backgrounds