Research Scientist, Eu Gts Network Design Analytics
il y a 6 jours
Interest and experience in Operations Research, and more specifically in discrete optimization, in fields such as Mixed-Integer Programming, Local Search and Constraint Programming.
- Experience with optimization solvers along with their implementation.
- Experience in Machine Learning and Deep Learning, not limited to the use of off-the-shelf solution, with the eagerness of developing your own models.
- Proven ability to code in a scripting language (Python/R...) for prototyping and a programming language (C/C++/Java...) for close to bare-metal performance.
- Interest in high coding standards: Git, CI/CD, unit testing, test-driven development
Have you ever wished to build high standard Operations Research and Machine Learning algorithms to optimize one of the most complex logistics network?
Have you ever ordered a product on Amazon websites and wondered how it got delivered to you so fast, and what kinds of algorithms & processes are running behind the scenes to power the whole operation? If so, this role is for you.
Amazon’s EU Global Transportation Services Network Design Analytics team is seeking a highly skilled Research Scientist. Your role will focus on solving complex problems that impact our organization, particularly in developing advanced models for optimizing Amazon’s transportation network.
**You are the person we are looking for if you have**:
- Good problem-solving abilities and technical curiosity.
- Commitment to high standards in code performance and inventiveness.
- Persistent ownership over research topics: you are proactive and bring your own ideas to the table.
- Excellent communication skills to engage with various stakeholders inside the company.
Key job responsibilities
- Use state-of-the-art optimization techniques from the scientific literature to develop optimization models that have a direct impact on the real-life transportation network.
- Explore pioneering modellings to solve the Amazon peculiar challenges, leveraging the access to data and computing power we have in house to bridge two seemingly separated fields: Operations Research and Machine Learning.
- Collaborate closely with various stakeholders to develop a deep understanding of the problem.
- Ensure your model can go to production by following high coding standards and seeking fast runtime.
A day in the life
You will typically engage in a mix of activities like conducting experiments, reviewing scientific literature, analyzing data, developing algorithms, collaborating with cross-functional teams, and often presenting findings. You will be involved in brainstorming sessions with your scientific peers, actively participate in code reviews and paper reviews. The day involves a blend of hands-on research, coding, meetings, data analysis, and contributions to publications.
About the team
Our team is a very dynamic technical team where we foment learning and development on top of all. We believe in learn by doing and having ownership are the best ways to develop knowledge and career. We are structured by functional skills and we partner and learn from one another.
Luxembourg, LUX
**ENGLISH VERSION**:
- Experience with stochastic and/or robust optimization.
- Experience in one of the following Machine Learning fields: Graph Neural Networks, Recurrent Neural Networks or Reinforcement Learning. Bonus point if these were used within an optimization context.
- Demonstrated ability to quickly learn new programming languages.
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