Data Scientist

Derby
4 months ago
Applications closed

Related Jobs

View all jobs

Data Scientist

Data Scientist

Data Scientist

Data Scientist

Data Scientist (Government)

Data Scientist - Renewable Energy

Data Scientist - £55,000-£70,000 - Remote

A fast-growing UK tech company is seeking a Data Scientist to join their dynamic team. This is a unique opportunity to be part of a business that's scaling rapidly and making waves in the e-commerce space.

This company has recently been recognised as one of the UK's fastest-growing tech firms. They want to be the best choice for every customer, everywhere. The team is collaborative, ambitious, and thrives in a fast-paced, ever-evolving environment. You'll be part of a close-knit group driving real change.

As their Data Scientist, you'll play a key role in identifying and quantifying potential risks through data-driven strategies and predictive modelling. You'll work closely with cross-functional teams to build tools and insights that support effective risk mitigation and informed decision-making.

Key Responsibilities:

Develop statistical and machine learning models to simulate risk scenarios.
Analyse large datasets to uncover trends and emerging risks.
Translate insights into actionable risk mitigation strategies.
Build dashboards and visualisations for stakeholders.
Collaborate with data engineers to ensure clean, integrated data.
Continuously refine models to adapt to evolving risk landscapes.Requirements:

Experience as a data scientist.
Strong Python and SQL skills.
Experience with machine learning frameworks and statistical analysis.
Knowledge of LLMs and AI modelling tools.
Excellent communication and problem-solving skills.
Comfortable working in a fast-paced, collaborative environment.Benefits:

Salary up to £70,000 depending on experience
Flexible working culture
Company equity
Opportunity to make a real impact in a high-growth tech company

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.