Insight Consultant - Data driven Solutions

MATTHEW OLIVERS LTD
London
1 year ago
Applications closed

Related Jobs

View all jobs

Managing Consultant - C&M - Data Science

Consultant, Data Science and Business Analyst, AI & Data, Defence & Security

Senior Data Scientist

Senior Data Scientist - AI Practice Team

Junior Data Scientist - AI Practice Team

Junior Data Scientist - AI Practice Team

  • Insight Consultant - Data driven solutions
  • Perm
  • London - Hybrid working
  • Salary - £60-70,000 + benefits

We are seeking a skilled Insight Consultant with a robust background in data solutions, to join our dynamic Data Consultancy team.

The ideal Consultant will possess a strong understanding of data integrations, migrations, roadmaps, operating models, and loyalty programs. You will work closely with Analytics, Data Science and wider Project teams to deliver end to end projects that meet and exceed client needs and expectations.

You will be involved in the end to end project process, from initial discovery stages - through to solution delivery.

The Consultant will need strong analytical skills, effective communication, and the ability to collaborate across departments are essential.

If you are passionate about delivering data-driven solutions and thrive in a fast-paced environment, apply and help us shape the future of data consulting.

Key Skills

  • Strong consulting experience, pitches, creating decks, discovery stages
  • Good data experience - knowledge of integrations, roadmaps, migrations, data strategy
  • Advanced Powerpoint, Excel experience
  • A good understanding of cloud platforms - Azure, AWS for example
  • Strong organisational skills, the ability to multi-task and track project life-cycles
  • Commercial and strategic mindset - ...

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.