Work From Home in Gomshall, Surrey, England - £500 - £3000+ per month, Full time or Part time.

Reps.co.uk
Gomshall
10 months ago
Applications closed

Related Jobs

View all jobs

Data Scientist - User Fraud

Junior Data Scientist Python SQL - HealthTech

Data Science Lead / Manager

Senior Data Scientist

Senior Machine Learning Engineer

Data Science and Innovation Manager

Work Your Own Hours to achieve the Work-Life balance & Income you want.

Home Based Opportunity with a leading UK Company UTILITY WAREHOUSE est. 2002

Part of the Telecom Plus group

  • Utilities are constantly rising.
  • Save money on essential services.
  • Help others save money and get paid.

Gas - Electricity - Broadband - Mobile & Insurance

This is a Self Employed Opportunity

  • Work around your existing job
  • And fit around family commitments
  • Potential earnings from £500-£3000 pcm
  • Unlimited income potential for team builders
  • Free ongoing training is provided

Initial nominal refundale fee of £10 is required

Earnings are dependant upon the effort and time you put in.

This is an opportunity to build for your financial security.
To apply, you MUST be permitted to work in the UK,
Minimum age 21 and not on a student VISA
This is NOT a warehouse Job

To find out more click APPLY NOW

A company representative will call to explain and answer your questions with no obligation interested then click apply now.

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.