Applied Scientist on Artificial Intelligence and Optimization, EU LTP Science (OCTPS)

At Amazon we are working to be the most customer-centric company on earth where customers can find and discover anything they might want to buy online. Our Supply Chain organization spans the entire Amazon fulfillment network from inventory placement and capacity planning through middle mile and last mile delivery. Our goal is to build a world class end-to-end supply chain that exceeds the expectations of our customers by ensuring their orders are delivered as quickly accurately and cost effectively as possible.

We are now looking to hire a passionate innovative and customer-obsessed candidate to support our end-to-end network planning and optimization across the Amazon supply chain. As an Applied Scientist you will work with software engineers product managers and business teams to understand the requirements and current challenges distill that understanding to elegantly define the problem and develop innovative solutions that integrate planning and execution across the entire fulfillment pipe. A central part of this mission is harnessing recent advances in Artificial Intelligence including machine learning large language models and generative AI to transform how we optimize the network and make decisions at scale.

Key job responsibilities
Solve complex optimization and machine learning problems using scalable algorithmic techniques.
Apply modern AI methods including generative and foundation models to improve optimization forecasting and automated decision making across the supply chain.
Design and develop efficient research prototypes that address real-world problems across Amazons end-to-end supply chain operations.
Lead complex time-bound long-term as well as ad-hoc analyses to assist decision making.
Communicate to leadership results from business analysis strategies and tactics including how AI-driven approaches change the way decisions are made.

A day in the life
The role will own the approval from senior functional leaders to enable strategies that improve processes and performance across the supply chain. You will be a natural self-starter who is comfortable supporting complex cross functional projects and action plans. You will have a true hands-on approach the ability to generate solutions strong process management skills and be an effective communicator.

- PhD or a Masters degree and experience in CS CE ML or related field
- Experience in building models for business application
- Experience in patents or publications at top-tier peer-reviewed conferences or journals
- Experience programming in Java C Python or related language
- Experience in any of the following areas: algorithms and data structures parsing numerical optimization data mining parallel and distributed computing high-performance computing

- Detailed knowledge of optimization methods including linear and mixed-integer programming network modeling constraint programming approximation algorithms and advanced heuristic techniques.
- Expertise on MIP strategies to customize and leverage commercial solvers and adapt them as required.
- Detailed knowledge of forecasting techniques with time-series tools including ARIMA models exponential smoothing LSTM and CNNs.
- Expertise on policy optimization techniques including reinforcement learning deep Q-learning bandits and online optimization.
- Experience applying modern AI methods such as large language models generative AI and foundation models to optimization forecasting or automated decision-making problems.
- Experience integrating machine learning and optimization to drive planning and execution decisions across an end-to-end supply chain.

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