Have you ever ordered a product on Amazon websites and wondered how it got delivered to you so fast, and what kinds of systems & processes are running behind the scenes to power the whole operation?
If so, this role is for you.
We need exceptionally bright, talented, and driven people to delight our customers.
If you'd like join the world’s largest online retailer, this is your chance to have fun and make history ! Role Overview The EU Supply Chain team is looking for a Senior Operations Research Scientist.
Within the EU Supply Chain Data Science team, you will develop new ways to tackle the trade offs we're facing to increase or speed to deliver to customers, reduce speed while managing the network physical constraints.
This role will give you a unique view on Amazon process and operations, interacting with other supply chain teams, planning teams, fulfillment centers and technical teams.
We want you to change the way we look at fulfillment so that we can delight our customers always more efficiently by guiding planning teams with data from models you'll develop.
If you are someone who has shown success in modelling, diving deep in complex data and pioneering new ways to do things, we’d like to talk to you.
This position is based out of our EU Headquarters in Luxembourg.
Responsibilities You own EU wide optimization projects within the EU Supply Chain and Analytics team.
You'll model and propose optimizations in the following areas : Trade off systematically cost of capacity with speed impact Understand the impact of network constraints on distance to customers Optimize our warehouse-
to-warehouse network to deliver the shortest distance to customers with minimal transfers BASIC QUALIFICATIONS Master degree in a scientific subject : operations research, management science, statistics, engineering, mathematics, or computer science 4 years of experience in a highly analytical environment Strong Operations Research background, with hands-
on experience in building supply chain / logistics systems prototypes Ability to perform quantitative, economic, and numerical analysis of the performance of these systems under uncertainty Experience with simulations to support operational decision-making.
Mastery of optimization techniques, including linear and non-linear programming, combinatorial optimization, integer and dynamic programming, network flows Experience with Matlab, Python and R and solvers (GUROBI, CPLEX,.
Organized, self-starter and a quick learner.
Must be an independent problem solver that can make high quality judgments and decisions quickly with excellent organization skills.
Must be detail-oriented with a demonstrated ability to self-motivate and follow-through on projects.
Excellent communicating skills coupled with ability to comfortably and confidently present to all levels within the company is required Experience of dealing with results, metrics and data management and desire to create and build new processes PREFERRED QUALIFICATIONS Hands-
on experience with commercial applications of machine learning techniques and tools Knowledge of SQL and visualisation tools (R shiny, Tableau, Qlikview, PowerBI)