At Amazon Supply Chain Europe, we are forecasting, planning, and optimizing in real time the flow of millions of products and orders each day across Europe throughout our fulfillment network.
We apply machine learning, operations research, and commons sense to large volumes of data and against a wide spectrum of problems.
In particular, the Supply Chain Automation team is paving the way towards an optimized and automated planning and execution of European operations.
This is a very exposed team at the cross-road between Retail, Operations, and Software Development. If you have experience with AI, including building ML or DL models, we’d like to have you join our team.
You will get to work with an innovative company, with great teammates, and have a lot of fun.
A successful candidate will be a person who enjoys diving deep into data, doing analysis, discovering root causes, and designing long-
term solutions. It will be a person who likes to have fun, loves to learn, and wants to innovate in the world of industry-AI.
A Masters Degree in a highly quantitative field (Computer Science, Machine Learning, Operational Research, Statistics, Mathematics, etc.
or equivalent experience
6+ years of experience working with large-scale, complex datasets to create / optimize machine learning, predictive, forecasting, and / or optimization models
Ability to write production level code in R or Python
Knowledge and experience of writing and tuning SQL
Practical understanding and hands-on experience with the following :
Supervised learning methods (linear and logistic regression, generalized linear models, decision trees, random forests, support vector machines, graphical models, neural networks / deep learning, etc.).
Unsupervised learning methods (K-means, hierarchical clustering, association rules, principal components, etc.).
Mathematical optimization (mixed integer programming, linear programming, stochastic programming / optimization discrete optimization convex optimization, reinforcement learning, etc.).
Track record of diving into data to discover hidden patterns and solving operational problems with data science
Past and current experience writing and speaking about complex technical concepts to broad audiences in a simplified format
PhD in a highly quantitative field (Computer Science, Machine Learning, Operational Research, Statistics, Mathematics, etc.)
Experience in building models based on Recurrent Neural Networks (e.g. LSTM) to forecast time series
8+ years of industry experience in predictive modeling and analysis
Good skills with programming languages, such as Java,C / C++, Scala
Experience with using data visualization tools (e.g. Tableau, Shiny, Django, d3.js)
Ability to develop experimental and analytic plans for data modeling processes, use of strong baselines, ability to accurately determine cause and effect relations
Experience with AWS technologies like Redshift, S3, EC2, Data Pipeline, Sagemaker, & EMR
Combination of deep technical skills and business savvy enough to interface with all levels and disciplines within our organization
Demonstrable track record of dealing well with ambiguity, prioritizing needs, and delivering results in a dynamic environment