Data Scientist

Glass.AI
greater london, england, united kingdom
9 months ago
Applications closed

Related Jobs

View all jobs

Data Scientist

Data Scientist

Data Scientist

Data Scientist

Data Scientist

Data Scientist

Join Our Mission to Read the Web and Research Companies With AI

Are you a curious and ambitious Computer Science graduate or a person with 1-2 years of work experience looking to launch your career in AI and data science? Join our growing team of world-class data scientists and AI engineers, and help us build technology that understands written language at scale.


We’re a UK-based company using cutting-edge AI to analyze the open web and surface valuable business insights on companies around the globe. Our technology is trusted by governments, top-tier consultancies, and leading corporations—making a real-world impact every day. As part of our team, you’ll work on innovative projects, tackle real-world data challenges, and collaborate closely with our CTO. This is a full-time role with a starting salaryof £40,000–£45,000and the opportunity to make a real impact from day one.


We work in a flexible hybrid model, part remote and part from our central London (Holborn) office.


What You'll Do

  • Dive into raw data to assess quality, clean, structure, and prepare it for downstream processing.
  • Design and implement scalable, high-performance prediction algorithms.
  • Collaborate with engineers to transform prototypes into robust, production-ready systems.
  • Deliver insights that drive strategic business decisions and improvements.


Qualifications

  • Bachelor's degree or experience in a quantitative field (Mathematics, Computer Science or Engineering).
  • At least 1 - 2 years of experience in quantitative analytics or data modelling.
  • Deep understanding of predictive modelling, machine learning, clustering and classification techniques.
  • Fluency in a programming language (Python, C, C++, Java, SQL).
  • Familiarity with Big Data frameworks and visualization tools (Cassandra, Hadoop, Spark, Tableau).

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.

Products

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.

Jobs

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.

Careers

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.

🍪 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.