Data Scientist

JR United Kingdom
Stoke-on-Trent
5 months ago
Applications closed

Related Jobs

View all jobs

Data Scientist

Data Scientist

Data Scientist

Data Scientist

Data Scientist

Data Scientist

Social network you want to login/join with:

A growing player in the ESG space is looking for a Data Scientist, with experience in the risk space, to shape and deliver analytics capabilities for their risk and ESG-focused product. This is a chance to join a data-led business with an abundance of unique internal datasets and real appetite to explore external sources to enhance its insight-driven platform.

Sitting within a collaborative, cross-functional team, you'll take ownership of building and deploying risk models that span from individual company assessments to broader supply chain evaluations. You’ll also play a key role in developing generative AI capabilities for insight reporting and contribute directly to new product development alongside Product, BI and wider Data Science teams.

Key Responsibilities

  • Build and implement risk models across companies and construction supply chains.
  • Source and analyse new datasets to drive product innovation and insight.
  • Collaborate with Product, BI and Data Science teams to deliver value to clients.
  • Lead GenAI-driven reporting for the risk product.
  • Communicate complex insights in a clear, commercial way.

What We’re Looking For

  • Strong skills in SQL and Python for data analysis and modelling.
  • Proactive mindset with the ability to operate autonomously.
  • Excellent communication skills for technical and non-technical audiences.
  • Experience in risk analysis, ideally in finance, insurance, or supply chains.
  • Knowledge of UK company law or insolvency risk is a bonus.
  • Experience with PowerBI or similar data visualisation tools.
  • Exposure to LLMs or generative AI for reporting is highly desirable.

If this looks like it could be of interest, apply below.


#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.

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.

What Hiring Managers Look for First in Machine Learning Job Applications (UK Guide)

Whether you’re applying for machine learning engineer, applied scientist, research scientist, ML Ops or data scientist roles, hiring managers scan applications quickly — often making decisions before they’ve read beyond the top third of your CV. In the competitive UK market, it’s not enough to list skills. You must send clear signals of relevance, delivery, impact, reasoning and readiness for production — and do it within the first few lines of your CV or portfolio. This guide walks you through exactly what hiring managers look for first in machine learning applications, how they evaluate CVs and portfolios, and what you can do to improve your chances of getting shortlisted at every stage — from your CV and LinkedIn profile to your cover letter and project portfolio.