Data Science Engineer

Roke
Woking
3 weeks ago
Applications closed

Related Jobs

View all jobs

Data Science Engineer

Data Science Engineer

Data Science Engineer

Data Science Engineer – Hybrid AI & MLOps

Data Science Engineer: End-to-End AI/ML Solutions

Senior Data Science Engineer

Data Science Engineer


National Security Business


Be part of a growing and highly trusted supplier into the NS domain working to deliver mission critical solutions helping to keep the nation safe, secure and prosperous.


Work on leading edge technology solutions in the following disciplines: AI & Data Science, Cyber, Cloud, Big Data, Software Development, DevOps, SRE, Platform Engineering.


Role

As a Data Science Engineer, you’ll be actively involved in development of mission critical technical solutions that focus on data services for our National Security customers.


As our next Data Science Engineer, you’ll be working with datasets of varying sizes to cleanse, manipulate, fuse and explore; allowing our customers to make faster, more accurate decisions and keep the nation safe.


The key requirements

  • Experience with scripting languages like Python for data exploration, cleansing and manipulation.
  • A knowledge of machine learning models and statistical techniques, including validation.
  • An understanding of data analytics and data visualisation techniques.
  • Able to process large datasets via batch or stream processing using Apache Spark or similar.
  • Exposure to techniques used for acquiring and fusing data.

The below skills and experience would also be a bonus :

  • Cloud platforms (preferably AWS) or implementing cloud-based data science solutions.
  • Knowledge of, or willingness to learn DataOps.
  • Structured or unstructured database experience.
  • Container experience, including Docker and Kubernetes.
  • Agile ways of working.
  • Software best practices including version control and CI / CD pipelines for automated testing and deployment.
  • Familiarity with linux.

Built on over a 60-year heritage, Roke offers specialist knowledge in sensors, communications, cyber, and AI and ML. We change the way organisations think and act – through dynamic insights from the analysis of multiple layers of data. We take care of the innovative, technical stuff that keeps everyone safe – that’s our mission, passion, and motivation.


We have secured long term work, across the full spectrum, on the latest framework with the client, which provides the springboard for our ongoing growth and development in this domain, so join us on what will be an incredible growth journey.


Where you’ll work

You’ll find our Woking site in a modern building on the outskirts of London. Rated excellent for sustainability by BREEAM & Fitwel certified – you’ll feel better for visiting. This site provides key links to our customers in London, is a 5-minute walk from the train station, has secure parking nearby and dedicated cycle storage.


There is an expectation that a significant proportion of your time will be spent working on customer sites in the London area.


Clearances

Due to the nature of this role, we require you to be eligible to achieve DV clearance. As a result, you should be a British Citizen and have resided in the for the last 10 years.


The next step

Click apply, submitting an up-to-date CV. We look forward to hearing from you.


#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.

Careers Jobs

Machine Learning Jobs for Career Switchers in Their 30s, 40s & 50s (UK Reality Check)

Are you considering a career change into machine learning in your 30s, 40s or 50s? You’re not alone. In the UK, organisations across industries such as finance, healthcare, retail, government & technology are investing in machine learning to improve decisions, automate processes & unlock new insights. But with all the hype, it can be hard to tell which roles are real job opportunities and which are just buzzwords. This article gives you a practical, UK-focused reality check: which machine learning roles truly exist, what skills employers really hire for, how long retraining realistically takes, how to position your experience and whether age matters in your favour or not. Whether you come from analytics, engineering, operations, research, compliance or business strategy, there is a credible route into machine learning if you approach it strategically.

Jobs

How to Write a Machine Learning Job Ad That Attracts the Right People

Machine learning now sits at the heart of many UK organisations, powering everything from recommendation engines and fraud detection to forecasting, automation and decision support. As adoption grows, so does demand for skilled machine learning professionals. Yet many employers struggle to attract the right candidates. Machine learning job adverts often generate high volumes of applications, but few applicants have the blend of modelling skill, engineering awareness and real-world experience the role actually requires. Meanwhile, strong machine learning engineers and scientists quietly avoid adverts that feel vague, inflated or confused. In most cases, the issue is not the talent market — it is the job advert itself. Machine learning professionals are analytical, technically rigorous and highly selective. A poorly written job ad signals unclear expectations and low ML maturity. A well-written one signals credibility, focus and a serious approach to applied machine learning. This guide explains how to write a machine learning job ad that attracts the right people, improves applicant quality and strengthens your employer brand.

Education Jobs

Maths for Machine Learning Jobs: The Only Topics You Actually Need (& How to Learn Them)

Machine learning job adverts in the UK love vague phrases like “strong maths” or “solid fundamentals”. That can make the whole field feel gatekept especially if you are a career changer or a student who has not touched maths since A level. Here is the practical truth. For most roles on MachineLearningJobs.co.uk such as Machine Learning Engineer, Applied Scientist, Data Scientist, NLP Engineer, Computer Vision Engineer or MLOps Engineer with modelling responsibilities the maths you actually use is concentrated in four areas: Linear algebra essentials (vectors, matrices, projections, PCA intuition) Probability & statistics (uncertainty, metrics, sampling, base rates) Calculus essentials (derivatives, chain rule, gradients, backprop intuition) Basic optimisation (loss functions, gradient descent, regularisation, tuning) If you can do those four things well you can build models, debug training, evaluate properly, explain trade-offs & sound credible in interviews. This guide gives you a clear scope plus a six-week learning plan, portfolio projects & resources so you can learn with momentum rather than drowning in theory.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.