Turnaround and Restructuring Strategy Graduate Programme

targetjobs Hired
Birmingham
1 year ago
Applications closed

Related Jobs

View all jobs

On Machine Learning Engineering Manager

Data Scientist KTP Associate

Programme overview

Organisations across the globe are facing unprecedented challenges. These challenges, amongst others, include macroeconomic and geopolitical changes, competitor innovation, supply chain risks and changing stakeholder expectations. we help organisations deal with these challenges, making a difference in a fast-paced environment.

Whether our clients are companies, government organisations, investors, or financial stakeholders and whether they’re a company in distress or simply seeking to build underlying resilience in their business, we work closely alongside them to deliver the financial and organisational outcomes that enable them to adapt and succeed.

You’ll learn how to work with visualisation and analytical tools, automation and artificial intelligence to deliver faster, more insightful client deliverables. Your technology experience is limited only by your imagination and your thirst to learn.


What you will be doing

  • Reviewing operational and business models.
  • Identifying strategic initiatives for companies.
  • Supporting with project management, proposals, business development activities and key deliverables.
  • Building strong stakeholder relationships with clients, external parties, and across the organisation.
  • Collaborating with other teams across the organisation to provide the best possible solution for our clients.

Requirements

We operate an open access policy, meaning we don’t screen out applications on your academic performance alone. You will, however, need to be working towards an honours degree in any subject, have a minimum of grade 4/C GCSE (or equivalent) in English Language and Maths, or in your home language if you do not hold English Language GCSE, and three A-levels/Five Highers (or equivalent) to be eligible to apply.

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.