DESCRIPTION
We (SCOT) are responsible for designing and planning the largest fulfillment network (Amazon) using Artificial Intelligence and Machine Learning techniques.
The team is composed of scientists, BIEs, Software Engineers, and Researchers who lead the industry in the development of innovative algorithms and strategies to maximize the long term effectiveness of Amazon's Retail business.
We are focused on using cutting edge science to improve customer outcomes and transform our logistics business. We own scalable distributed systems in the cloud that use real time, large scale 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 costs.
As the Fulfillment Network Planning team, 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 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. Every member of the team needs to have innovative thinking, a burning desire to learn, and the skills and experience needed to build science and technology so advanced that it will appear to generate "magical outcomes"..
Job Responsibilities Include
- Defining, developing and maintaining critical business and operational reports reviewed on a weekly, monthly, quarterly, and annual basis
- Analysis of historical data to identify trends and support decision making, including written and verbal presentation of results and recommendations
- Collaborating with software development teams to implement analytics systems and data structures to support large-scale data analysis and delivery of machine learning and econometric models
- Mining and manipulating data from database tables, simulation results, and log files
- Identifying data needs and driving data quality improvement projects
- Understanding the broad range of Amazon's data resources, which to use, how, and when
- Thought leadership on data mining and analysis
To help describe some of our challenges, we created a short video about Supply Chain Optimization at Amazon -
We are open to hiring candidates to work out of one of the following locations:
Bellevue, WA, USA 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
