Amazon Applied Scientist EU STEP Science Tech 

Luxembourg, Luxembourg 

491554483

The job is opened in the EU Headquarters in Luxembourg (alternatively: Barcelona, Berlin or London), designed to maximize interaction with the team and stakeholders, but we will consider applicants with remote work requirements as well.Basic qualifications
* PhD in Operations Research, Machine Learning, Statistics, Applied Mathematics, Computer Science or other field related to algorithms and data (or equivalent experience).
* Excellent written and verbal communication skills.
* Experience with some programming language (Java/python/C++)
* Research experience in one or more:
*Combinatorial optimization problems (e.g., scheduling, vehicle routing, facility location). *Continuous optimization problems (e.g., linear programming, convex programming, non-convex programming).
Preferred qualifications
* Experience from working in a fast-paced applied research environment.
* Ability to handle ambiguity.
* Top tier publications pertinent to the field of study.
Key job responsibilities
Solve complex optimization and machine learning problems using scalable algorithmic techniques.Lead complex time-bound, long-term as well as ad-hoc analyses to assist decision making.A day in the life
You will be brainstorming algorithmic approaches with team-mates to solve challenging problems for Amazon logistics operations.You will be developing and testing prototype solutions with above algorithmic techniques.You will be scavenging information from the sea of Amazon data to improve these solutions.You will be meeting with other scientists, engineers, stakeholders and customers to enhance the solutions and get them adopted.
We use modular algorithmic designs in the domain of combinatorial optimization, solving complicated generalizations of core OR problems with the right level of decomposition, employing parallelization and approximation algorithms.We use deep learning, bandits, and reinforcement learning to put data into the loop of decision making.We code our prototypes to be production-readyWe prefer provably optimal solutions than heuristics, though we settle for heuristics when performance dictates it. Overall, we appreciate the value of correct modeling.

- PhD
- Experience in patents or publications at top-tier peer-reviewed conferences or journals
- Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing
- Experience programming in Java, C++, Python or related language

- Experience using Unix/Linux
- Experience in professional software development