2025 Data Scientist Internship (multiple locations), Amazon University Talent Acquisition

Amazon UK Services Ltd. - A10
London
1 month ago
Applications closed

Related Jobs

View all jobs

Digital and IT Intern- Data Science

Senior Data Scientist

Principal Data Scientist

Principal Data Scientist - NLP

Principal Data Scientist and Senior Data Engineer

Senior Data Scientist – Machine Learning -  Defence –Eligible for SC

Are you a MS or PhD student interested in a 2025 Internship in Data Science? If so, we want to hear from you!

We are looking for a customer obsessed Data Scientist Intern who can innovate in a business environment, building and deploying machine learning models to drive step-change innovation and scale it to the EU/worldwide.

If this describes you, come and join our Data Science teams at Amazon for an exciting internship opportunity. If you are insatiably curious and always want to learn more, then you’ve come to the right place.

You can find more information about the Amazon Science community as well as our interview process via the links below;






Key job responsibilities
As a Data Science Intern, you will have following key job responsibilities:

•Work closely with scientists and engineers to architect and develop new algorithms to implement scientific solutions for Amazon problems.
•Work on an interdisciplinary team on customer-obsessed research
•Experience Amazon's customer-focused culture
•Create and Deliver Machine Learning projects that can be quickly applied starting locally and scaled to EU/worldwide
•Build and deploy Machine Learning models using large data-sets and cloud technology.
•Create and share with audiences of varying levels technical papers and presentations
•Define metrics and design algorithms to estimate customer satisfaction and engagement


A day in the life
At Amazon, you will grow into the high impact, visionary person you know you’re ready to be. Every day will be filled with developing new skills and achieving personal growth.
How often can you say that your work changes the world? At Amazon, you’ll say it often. Join us and define tomorrow.
Some more benefits of an Amazon Science internship include;
•All of our internships offer a competitive stipend/salary
•Interns are paired with an experienced manager and mentor(s)
•Interns receive invitations to different events such as intern program initiatives or site events
•Interns can build their professional and personal network with other Amazon Scientists
•Interns can potentially publish work at top tier conferences each year


About the team
Applicants will be reviewed on a rolling basis and are assigned to teams aligned with their research interests and experience prior to interviews. Start dates are available throughout the year and durations can vary in length from 3-6 months for full time internships.
This role may available across multiple locations in the EMEA region (Austria, France, Germany, Ireland, Israel, Italy, Luxembourg, Netherlands, Poland, Romania, Spain and the UK).
Please note these are not remote internships.

BASIC QUALIFICATIONS

- Are enrolled in a Master's degree in computer science, machine learning, engineering, or related fields
- Speak, write, and read fluently in English

PREFERRED QUALIFICATIONS

- Experience in at least one of the related science disciplines (optimization - LP, MIP, statistics, machine learning, process control, combinatorial optimization)
- Experience with data scripting languages (e.g., SQL, Python, R, or equivalent) or statistical/mathematical software (e.g., R, SAS, Matlab, or equivalent)
- Experience with big data: processing, filtering, and presenting large quantities (100K to Millions of rows) of data
- Experience implementing algorithms using both toolkits and self-developed code

Get the latest insights and jobs direct. Sign up for our newsletter.

By subscribing you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Machine‑Learning Jobs for Non‑Technical Professionals: Where Do You Fit In?

The Model Needs More Than Math When ChatGPT went viral and London start‑ups raised seed rounds around “foundation models,” many professionals asked, “Do I need to learn PyTorch to work in machine learning?” The answer is no. According to the Turing Institute’s UK ML Industry Survey 2024, 39 % of advertised ML roles focus on strategy, compliance, product or operations rather than writing code. As models move from proof‑of‑concept to production, demand surges for specialists who translate algorithms into business value, manage risk and drive adoption. This guide reveals the fastest‑growing non‑coding ML roles, the transferable skills you may already have, real transition stories and a 90‑day action plan—no gradient descent necessary.

Quantexa Machine‑Learning Jobs in 2025: Your Complete UK Guide to Joining the Decision‑Intelligence Revolution

Money‑laundering rings, sanctioned entities, synthetic identities—complex risks hide in plain sight inside data. Quantexa, a London‑born scale‑up now valued at US $2.2 bn (Series F, August 2024), solves that problem with contextual decision‑intelligence (DI): graph analytics, entity resolution and machine learning stitched into a single platform. Banks, insurers, telecoms and governments from HSBC to HMRC use Quantexa to spot fraud, combat financial crime and optimise customer engagement. With the launch of Quantexa AI Studio in February 2025—bringing generative AI co‑pilots and large‑scale Graph Neural Networks (GNNs) to the platform—the company is hiring at record pace. The Quantexa careers portal lists 450+ open roles worldwide, over 220 in the UK across data science, software engineering, ML Ops and client delivery. Whether you are a graduate data scientist fluent in Python, a Scala veteran who loves Spark or a solutions architect who can turn messy data into knowledge graphs, this guide explains how to land a Quantexa machine‑learning job in 2025.

Machine Learning vs. Deep Learning vs. MLOps Jobs: Which Path Should You Choose?

Machine Learning (ML) continues to transform how businesses operate, from personalised product recommendations to automated fraud detection. As ML adoption accelerates in nearly every industry—finance, healthcare, retail, automotive, and beyond—the demand for professionals with specialised ML skills is surging. Yet as you browse Machine Learning jobs on www.machinelearningjobs.co.uk, you may encounter multiple sub-disciplines, such as Deep Learning and MLOps. Each of these fields offers unique challenges, requires a distinct skill set, and can lead to a rewarding career path. So how do Machine Learning, Deep Learning, and MLOps differ? And which area best aligns with your talents and aspirations? This comprehensive guide will define each field, highlight overlaps and differences, discuss salary ranges and typical responsibilities, and explore real-world examples. By the end, you’ll have a clearer vision of which career track suits you—whether you prefer building foundational ML models, pushing the boundaries of neural network performance, or orchestrating robust ML pipelines at scale.