Data Scientist

Sirius Digital Services
Hampshire
1 year ago
Applications closed

Related Jobs

View all jobs

Data Scientist

Data Scientist

Data Scientist

Data Scientist

Data Scientist

Data Scientist

Data Scientist / Senior Data Scientist

Salary: from £40,000 (plus benefits, pension (7% contribution), 25 days holiday & life insurance)

Location: London or South West Region


We are looking for a Data Scientist consultant to join our growing Digital and Data Science division to be part of Sirius Digital. Sirius Digital provide a bespoke, robust and high-performance software to meet and exceed user requirements. We specialise in Software Engineering, Modelling & Simulation, Robotics & Autonomous Systems, Synthetic Environments, and AI & Machine Learning (ML).


Our team provides, adaptable and highly skilled capability, with a range of specialities to ensure that the right techniques are used to solve your problem.


The Role:

As a Data Scientist, you will play a major role in developing and implementing Machine Learning (ML) and Artificial Intelligence (AI) models, along with providing key advice around innovation and new techniques to stakeholders. You will be designing solutions for complex challenges and will integrate code with software engineers.


Responsibilities will include:

  • Delivering technical consulting projects.
  • Developing and delivering AI / ML solutions using a large range of techniques (e.g. ML, NLP, LLMs, Motion Capture, Image Recognition, OCR, …)
  • Building new relationships and maintaining current customer relationships.
  • Applying mathematical and computational methods to tackle real world problems, applying tools and techniques, and developing novel approaches where required.


Expertise Required:

We are looking for a range of experience:

Data Scientist: 2+ years’ experience, including developing ML / AI projects.Senior Data Scientist: 5+ years’ experience, including productionising ML / AI projects.

About You:

The successful candidate must be able to demonstrate the following attributes:


Essential

  • Ability to understand and describe a range of data science techniques.
  • Experience in managing data and implementing data science processes.
  • Ability to apply knowledge in statistics and machine learning to real world problems.
  • Experience in translating customer requirements into quantitative models.
  • Experience in one or more of the following technical disciplines:
  1. Natural language Processing (NLP)
  2. ML (e.g. Random Forests, CatBoost, LXGM, …)
  3. Image Recognition
  4. Optical Character Recognition (OCR)
  5. Motion Capture
  • Proficient in Python, R or C++, including relevant libraries (numpy, pandas, matplotlib, Scikit-learm, tensorflow, etc…).
  • Proficient in a range of database protocols (e.g. SQL, noSQL).
  • Develop testing routines or procedures.
  • Building customer and stakeholder relationships.
  • Supporting and leading authoring of technical reports and presenting to customers.
  • Be willing to travel across UK and comfortable to work away from home for periods of time.


Desirable:

The ideal candidate will be educated to degree level or have equivalent relevant experience.

Experience with Docker and/or Kubernetes (K8S)

Experience with Computer Vision (CV)

Experience with air-gapped systems

We’d love you to bring a strong STEM / computing background.


What we offer

We offer a combination of mentoring and internal and external training opportunities, with specialist sector organisations and in-house courses. You will have exposure to subject matter experts and additional online learning packages.


The role comes with a competitive benefits package including pension (7% company contribution), additional holiday purchase options, private health care, life assurance and electric vehicle scheme

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.