Data Scientist - Hybrid

Exposed Solutions
Windsor, City of Belfast, County Antrim
7 months ago
Applications closed

Related Jobs

View all jobs

Data Scientist

Hays Technology London, United Kingdom
£600 – £1,000 pd

Data Scientist

ISR Recruitment Exeter, Devon, United Kingdom
£50,000 – £60,000 pa Hybrid

Data Scientist

Faculty AI London, United Kingdom
Hybrid

Data Scientist

Vallum Associates London, United Kingdom

Data Scientist

Randstad Technologies Recruitment London, United Kingdom

Data Scientist

Access Computer Consulting City of London, United Kingdom
Posted
18 Sep 2025 (7 months ago)

Our client, a dynamic and innovative data and analytics organisation, is seeking an experienced Data Scientist to join their growing team. This is an excellent opportunity for a candidate who thrives on solving complex problems with data and is motivated by the transformative impact that Data and AI can deliver within organisations.

Key Responsibilities

  • Deliver high-quality data science and analytics solutions, contributing to design, development, and product roadmaps.

  • Collaborate with clients and internal teams to gather requirements, analyse data, and validate solutions.

  • Develop and implement descriptive, predictive, and prescriptive analytics, integrating data from multiple sources.

  • Produce clear documentation, reports, and visualisations.

  • Provide technical input for proposals, solution scoping, and proofs-of-concept.

  • Attend occasional client meetings or events across the UK, Europe, and internationally.

    Required Experience

  • Strong knowledge of data modelling, machine learning, and/or advanced data analytics.

  • Demonstrable track record of delivering data analytics projects as part of a team.

  • Hands-on experience with collaborative software development and version control (preferably Git).

  • Familiarity with Agile/SCRUM methodologies.

  • Exposure to pre-engagement activities such as project scoping, technical feasibility analysis, or prototype development.

  • Comfortable contributing to technical discussions and implementing solutions defined by project leads.

    Desirable Experience

  • Strong Python expertise.

  • Experience with GNU/Linux environments.

  • Familiarity with key data science and ML frameworks (e.g., scikit-learn, PyTorch, TensorFlow, XGBoost, Hugging Face).

  • Experience in natural language processing, tabular data analysis, or computer vision.

  • SQL proficiency.

  • Exposure to containerisation (Docker, Kubernetes) and cloud-native architectures.

  • Experience with CI/CD, automated testing, and iterative product development.

  • Knowledge of graph databases and graph analysis.

    Benefits

    Our client offers an exciting and supportive environment with a strong focus on employee wellbeing and career development. Benefits include:

  • 35 days annual leave (including public holidays) plus up to 10 days unpaid leave.

  • Flexible working arrangements around core hours.

  • Private health insurance and pension scheme.

  • Contribution to gym membership.

  • Ongoing professional development support (courses, certifications, conferences).

  • Regular company outings, team celebrations, and knowledge-sharing sessions.

  • Monthly recognition of outstanding performance.

    ALL APPLICANTS MUST BE FREE TO WORK IN THE UK.

    Exposed Solutions is acting as an employment agency to this client. Please note that no terminology in this advert is intended to discriminate on any grounds and we confirm that we will gladly accept applications from any persons for this role

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.