Senior Applied Scientist, EU ATS Science and Tech - Optimization

Amazon EU SARL (UK Branch); London; On-site; GBP 80,000 - 100,000; Full time

Job summary

A leading e-commerce company in London is looking for a Senior Applied Scientist to optimize logistics through algorithmic solutions and machine learning. The role requires a Master's degree and programming experience in Java, C++, or Python. Candidates should have a strong background in neural networks and applied research, with the ability to tackle complex business challenges. Join a team that innovatively drives Amazon's logistics efficiency.

Qualifications

• Experience programming in Java, C++, Python or related languages.
• Experience with neural deep learning methods and machine learning.
• Experience in building machine learning models for business applications.
• Experience in applied research.

Responsibilities

• Solve complex optimization and machine learning problems using algorithmic techniques.
• Design and develop efficient research prototypes addressing real-world problems.
• Lead analyses to assist decision making.
• Communicate results from business analysis to leadership.

Skills

Programming in Java

C++ programming

Python programming

Neural deep learning methods

Machine learning

Applied research

Education

Master's degree

Tools

R

scikit-learn

Spark MLLib

MxNet

Tensorflow

numpy

scipy

Job description

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Senior Applied Scientist, EU ATS Science and Tech - Optimization, London

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Client:

Amazon EU SARL (UK Branch)

Location:

London, United Kingdom

Job Category:

Other

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EU work permit required:

Yes

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Job Reference:

49e72551831f

Job Views:

8

Posted:

12.08.2025

Expiry Date:

26.09.2025

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Job Description:

Have you ever wondered how Amazon delivers timely and reliably hundreds of millions of packages to customer’s doorsteps? Are you passionate about data and mathematics, and hope to impact the experience of millions of customers? Are you obsessed with designing simple algorithmic solutions to very challenging problems?

If so, we look forward to hearing from you!

Amazon STEP Science and Tech is seeking Applied (or Research) Scientists. As a key member of the central Research Science Team of logistics operations, these persons will be responsible for designing algorithmic solutions based on data and mathematics for optimizing the end-to-end Amazon supply chain network.

The job is opened in the EU Headquarters in Luxembourg (alternatively: Barcelona or Berlin or London), designed to maximize interaction with the team and stakeholders.

Key job responsibilities

• Solve complex optimization and machine learning problems using scalable algorithmic techniques.
• Design and develop efficient research prototypes that address real-world problems in the massive logistics network of Amazon.
• 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.

A day in the life

• Brainstorm algorithmic approaches with team-mates to solve challenging problems for Amazon logistics operations.
• Develop and test prototype solutions with advanced algorithmic techniques.
• Gather information from Amazon data to improve these solutions.
• Meet with scientists, engineers, stakeholders, and customers to enhance and adopt solutions.

About the team

The Science and Tech (SnT) team of EU STEP aims to impact the world with mathematical and data-driven skills. We are the End-to-End Supply Chain optimizers, growing Amazon's logistics to support decision-making in a complex, data-driven ecosystem.

Our algorithms provide leadership confidence to invest hundreds of millions of euros annually. We enjoy solving real-world problems quickly, learning from failures, and innovating with modular algorithms, deep learning, bandits, and reinforcement learning. We collaborate closely with Amazon scholars and academic institutions, aiming to develop production-ready prototypes that balance optimality and performance.

BASIC QUALIFICATIONS

• Master's degree
• Experience programming in Java, C++, Python or related languages
• Experience with neural deep learning methods and machine learning
• Experience in building machine learning models for business applications
• Experience in applied research

PREFERRED QUALIFICATIONS

• Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, TensorFlow, numpy, scipy
• Experience with large-scale distributed systems such as Hadoop, Spark