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- Excellent written and verbal communication skills. Ability to communicate at a level appropriate to the audience.
- Experience designing and implementing models and algorithms for one or more 1) Combinatorial optimization problems (e.g., scheduling, vehicle routing, and facility location), 2) Continuous optimization problems (e.g., linear programming, convex programming, nonconvex programming), 3) Predictive analytics (e.g., forecasting, timeseries, neural networks), 4) Prescriptive analytics (e.g., stochastic optimization, bandits, reinforcement learning)
- Experience implementing algorithms in traditional programming languages (C++/ Java/ python)
- Comfortable to tradeoff complexity and efficiency of solution methodologies, according to the requirements of the problem. Ability to deal with ambiguity.
If so, we look forward to hearing from you
Amazon Transportation Services is seeking an Applied Scientist to be based in the EU Headquarters in Luxembourg.
As a key member of the Research Science Team of ATS operations, this person will be responsible for designing algorithmic solutions based on data and mathematics for optimizing the middle-mile Amazon Transportation Network.
The successful applicant will ensure that our end-to-end strategies in terms of customer demand fulfillment, routing, consolidation locations, linehaul/airhaul/sea options and last-mile transportation are streamlined and optimized.
This critical role requires an aptitude for independent initiative and decision-making, the ability to drive innovation in Transportation modelling and optimization across Amazon's expanding European network and linking into global initiatives and expansion strategies.
- Design and prototype algorithmic solutions for standardized processes.
- Lead complex timebound, longterm as well as adhoc transportation modelling analyses to help management in decision making.
- Partner with the planning, linehaul/airhaul and sort center operations teams, while working closely with lastmile, supply chain, and global delivery departments for modeling and optimizing the transportation network of EU.
Amazon is an Equal Opportunity-Affirmative Action Employer - Minority / Female / Disability / Veteran / Gender Identity / Sexual Orientation.
- Detailed knowledge of optimization methods including linear and mixedinteger programming, network modeling, constraint programming, approximation algorithms, and advanced heuristic techniques.
- Expertise on MIP strategies to customize and leverage commercial algorithms and adapt them as required.
- Detailed knowledge of forecasting techniques with timeseries tools, including ARIMA models, exponential smoothing, LSTM, CNNs.
- Expertise on policy optimization techniques, including reinforcement learning, deep Qlearning, bandits, and online optimization.
- Experience implementing models and analysis tools through the use of highlevel modeling languages (e.g. R, Matlab as examples).
- Experience collecting, processing and combining big data with appropriate methodologies (e.g. Hadoop, Map-Reduce)
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