DATA SCIENTIST

Atos SE
London
1 year ago
Applications closed

Related Jobs

View all jobs

Data Scientist

Data Scientist

Data Scientist

Data Scientist

Data Scientist

Data Scientist

Eviden, part of the Atos Group, with an annual revenue of circa € 5 billion, is a global leader in data-driven, trusted and sustainable digital transformation. As a next generation digital business with worldwide leading positions in digital, cloud, data, advanced computing, and security, it brings deep expertise for all industries in more than 47 countries. By uniting unique high-end technologies across the full digital continuum with 47,000 world-class talents, Eviden expands the possibilities of data and technology, now and for generations to come.

The Opportunity:

The Artificial Intelligence and Machine Learning team blend statistical techniques and ML to create value from data for our clients.

You will collaborate with business stakeholders to identify use cases and shape opportunities for delivering data science solutions, ensuring a clear connection to business benefits.

You'll extract, analyse and interpret large amounts of data from a range of sources, using algorithmic, data mining, artificial intelligence, machine learning, and statistical tools, in order to make it accessible to our clients. You will then present your results using clear and engaging language in a way that bridges the fundamentally theoretical aspects of these initiatives to the business needs. This includes translating between technical and nontechnical audiences.

You will work across industries and technology platforms (Azure, AWS, GCP) working with structured and unstructured data from an array of data sources.

Lead and deliver innovative technical solutions that will meet the requirements of our clients. This will entail gathering requirements, analysing, developing, testing, evaluating and deploying the appropriate solution through the full development lifecycle.

Maintain clear and coherent communication, both verbal and written, to understand data needs and report results to technical and non-technical audiences.

Horizon scan to stay up to date with the latest technology, techniques, and methods.

Conduct research from which you'll develop prototypes and proof of concepts.

Manage and mentor junior team members.

Person Specification

Extensive experience in comprehending business challenges and converting this understanding into practical data science solutions.

Previous experience of delivering data science solutions using Microsoft Fabric and Azure DevOps or similar.

Passionate about the transformative impact the right information can have on a business.

Strong grasp of statistical methods, experimental design, and the underlying principles of machine learning algorithms.

Ability to transform, analyse and model data from a variety of data sources, extracting and interpreting trends and insights.

Able to evaluate the models and experience of implementing them as stand-alone apps and as part of enterprise technology stacks. DataOps / MLOps experience would be valued.

Strong Python programming for modelling and/or data analysis is essential, preferably with experience using the spaCy NLP framework and BERT.

Knowledge of database design as well as strong experience with SQL queries is desirable. Familiarity with R and other common languages and tools would be beneficial.

Proficiency in stakeholder management and an effective, persuasive communication style to explain technical subjects to non-technical audiences.

Background in Mathematics or Physics and experience working within Agile projects as a team member and Scrum Master.

We care about our employees' happiness by:

  • 25 days of Annual leave + an option to purchase more through our Flexible Benefits.
  • Flex benefits system – an exciting opportunity to choose your own benefits.
  • Pension - matching contribution up to 10%.
  • Private Medical Scheme.
  • Life Assurance.
  • Enrolment in our Share scheme - subject to scheme eligibility criteria.
  • Unlimited opportunities to learn in our Training platforms.

As a Disability Confident employer, we aim to ensure that people with disabilities who meet the minimum criteria for this position will be offered an interview. We are committed to making reasonable adjustments and changes as needed to the application and assessment process to remove or reduce any disadvantage associated with a person's disability.

#J-18808-Ljbffr

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

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

Industry Insights

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

How Many AI Tools Do You Need to Know to Get an AI Job?

If you are job hunting in AI right now it can feel like you are drowning in tools. Every week there is a new framework, a new “must-learn” platform or a new productivity app that everyone on LinkedIn seems to be using. The result is predictable: job seekers panic-learn a long list of tools without actually getting better at delivering outcomes. Here is the truth most hiring managers will quietly agree with. They do not hire you because you know 27 tools. They hire you because you can solve a problem, communicate trade-offs, ship something reliable and improve it with feedback. Tools matter, but only in service of outcomes. So how many AI tools do you actually need to know? For most AI job seekers: fewer than you think. You need a tight core toolkit plus a role-specific layer. Everything else is optional. This guide breaks it down clearly, gives you a simple framework to choose what to learn and shows you how to present your toolset on your CV, portfolio and interviews.

What Hiring Managers Look for First in AI Job Applications (UK Guide)

Hiring managers do not start by reading your CV line-by-line. They scan for signals. In AI roles especially, they are looking for proof that you can ship, learn fast, communicate clearly & work safely with data and systems. The best applications make those signals obvious in the first 10–20 seconds. This guide breaks down what hiring managers typically look for first in AI applications in the UK market, how to present it on your CV, LinkedIn & portfolio, and the most common reasons strong candidates get overlooked. Use it as a checklist to tighten your application before you click apply.

The Skills Gap in AI Jobs: What Universities Aren’t Teaching

Artificial intelligence is no longer a future concept. It is already reshaping how businesses operate, how decisions are made, and how entire industries compete. From finance and healthcare to retail, manufacturing, defence, and climate science, AI is embedded in critical systems across the UK economy. Yet despite unprecedented demand for AI talent, employers continue to report severe recruitment challenges. Vacancies remain open for months. Salaries rise year on year. Candidates with impressive academic credentials often fail technical interviews. At the heart of this disconnect lies a growing and uncomfortable truth: Universities are not fully preparing graduates for real-world AI jobs. This article explores the AI skills gap in depth—what is missing from many university programmes, why the gap persists, what employers actually want, and how jobseekers can bridge the divide to build a successful career in artificial intelligence.