Data Scientist / AI Engineer

Searchability NS&D
Cheltenham, United Kingdom
Today
£45,000 – £95,000 pa

Salary

£45,000 – £95,000 pa

Job Type
Permanent
Work Pattern
Full-time
Work Location
On-site
Seniority
Junior
Education
Degree
Security Clearance
Required
Posted
30 Apr 2026 (Today)

Benefits

15% clearance bonus
  • Must have active enhanced DV (West) Clearance
  • Junior to Lead levels available
  • £45k to £95k DoE plus 15% clearance bonus
  • Must be willing to be full-time on-site in Cheltenham
  • Skills required in machine learning, GenAI, NLP, Customer Engagement/Consultancy

Who are we?

We are recruiting Junior, Senior and Lead Data Scientists with AI specialism and enhanced DV Clearance for a prestigious client to work on a portfolio of public and private sector projects. Our client is a global leader in technology, consulting, and engineering services at the forefront of innovation to evolve the world of digital, cloud, and platforms. You'll experience excellent career progression opportunities to develop your skillset and personal profile in an inclusive culture.

What will the Data Scientist be doing?

Our client is seeking individuals with strong technical expertise in machine learning, GenAI, computer vision, and data science, alongside solid skills in solution architecture and software engineering to design and scale impactful solutions. This role involves working closely with clients to identify challenges, define solutions, communicate their value clearly, and lead teams to successful delivery. There are also opportunities to publish whitepapers and represent the organisation at conferences, all within an inclusive and diverse working environment.

Key Skills and Requirements:

  • Proficient in AI techniques including machine learning, GenAI, NLP, deep learning, graph analytics, and time series analysis.
  • Strong communicator with the ability to simplify complex concepts, manage stakeholders, and motivate/lead Agile teams to deliver robust outcomes.
  • Experienced in securing work through RFI/RFPs, bids, and presentations across public and private sectors.
  • Skilled in data science platforms (e.g. Databricks, AzureML) and cloud services (AWS, Azure, GCP), with knowledge of tools like Terraform.
  • Experienced in deploying solutions using Docker, Kubernetes, CI/CD tools.

To be Considered:

Please either apply by clicking online or emailing me directly at . For further information please call me on or - I can make myself available outside of normal working hours to suit from 7 am until 10 pm. If unavailable, please leave a message and either myself or one of my colleagues will respond. By applying for this role, you give express consent for us to process & submit (subject to required skills) your application to our client in conjunction with this vacancy only. Also feel free to connect with me on LinkedIn, just search for Henry Clay-Davies. I look forward to hearing from you.

KEY SKILLS:

Data Science / Data Scientist / AI Engineer / AI / Machine Learning / ML / NLP / GenAI / Stakeholder Engagement / Customer Engagement / AWS / Azure / Cloud / Docker / Kubernetes / CI/CD / Deep Learning

Related Jobs

View all jobs

Senior Data Scientist

Harnham - Data & Analytics Recruitment Manchester, United Kingdom
£70,000 – £90,000 pa On-site

Graduate AI Data Scientist

Global Tech Recruitment London, United Kingdom
£42,000 – £45,000 pa Hybrid

Data Scientist

Oscar Technology London, United Kingdom
£65,000 – £75,000 pa Hybrid

Data Scientist / Algorithm Engineer

PhysicsX United Kingdom

Lead Data Scientist - Customer Development

Faculty AI London, United Kingdom
£80,000 – £120,000 pa Hybrid

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.

Where to Advertise Machine Learning Jobs in the UK (2026 Guide)

Advertising machine learning jobs in the UK requires a different approach to most technical hiring. The candidate pool is small, highly specialised and in demand across AI labs, financial services, healthcare, autonomous systems and consumer technology simultaneously. Machine learning engineers and researchers move between roles through professional networks, conference communities and specialist platforms — not general job boards where ML roles compete with unrelated software engineering positions for the same audience. This guide, published by MachineLearningJobs.co.uk, covers where to advertise machine learning roles in the UK in 2026, how the main platforms compare, what employers should expect to pay, and what the data says about hiring across different role types.

New Machine Learning Employers to Watch in 2026: UK and Global Companies Driving ML Innovation

Machine learning (ML) has transitioned from a specialised field into a core business capability. In 2026, organisations across healthcare, finance, robotics, autonomous systems, natural language processing, and analytics are expanding their machine learning teams to build scalable intelligent products and services. For professionals exploring opportunities on www.MachineLearningJobs.co.uk , understanding the companies that are scaling, winning investment, or securing high‑impact contracts is crucial. This article highlights the new and high‑growth machine learning employers to watch in 2026, focusing on UK innovators, international firms with significant UK presence, and global platforms investing in machine learning talent locally.

How Many Machine Learning Tools Do You Need to Know to Get a Machine Learning Job?

Machine learning is one of the most exciting and rapidly growing areas of tech. But for job seekers it can also feel like a maze of tools, frameworks and platforms. One job advert wants TensorFlow and Keras. Another mentions PyTorch, scikit-learn and Spark. A third lists Mlflow, Docker, Kubernetes and more. With so many names out there, it’s easy to fall into the trap of thinking you must learn everything just to be competitive. Here’s the honest truth most machine learning hiring managers won’t say out loud: 👉 They don’t hire you because you know every tool. They hire you because you can solve real problems with the tools you know. Tools are important — no doubt — but context, judgement and outcomes matter far more. So how many machine learning tools do you actually need to know to get a job? For most job seekers, the real number is far smaller than you think — and more logically grouped. This guide breaks down exactly what employers expect, which tools are core, which are role-specific, and how to structure your learning for real career results.