Entry Level Data Analyst

Derby
8 months ago
Applications closed

Related Jobs

View all jobs

Data Scientist Consultant - Graduate/Entry Level

Data Scientist Consultant - Graduate/Entry Level

Junior Data Scientist

Junior Data Scientist

Data Scientist No experience necessary

Data Science Trainee

Our client—a leading tech firm at the forefront of innovation—is looking for an enthusiastic Entry-Level Data Analyst to join their growing analytics team. This is a fantastic opportunity to transform your curiosity and analytical mindset into real-world business impact.

What You’ll Do:

  • Collect, clean, and structure data for analysis and reporting.

  • Build dashboards and reports using Excel, SQL, and data visualisation tools (e.g. Power BI, Tableau).

  • Identify trends, patterns, and actionable insights to support strategic decisions.

  • Assist in automating data processes and enhancing analytics systems.

  • Translate business challenges into data-driven solutions.

    Who We’re Looking For:

  • A degree in Data Science, Mathematics, Statistics, Computer Science, or a related field.

  • Comfortable with Excel and basic SQL; knowledge of Power BI or Tableau is a plus.

  • A sharp analytical thinker with strong attention to detail.

  • Clear communicator who can explain technical findings to non-technical stakeholders.

  • Proactive, self-motivated, and eager to learn in a fast-paced environment.

    What’s in It for You:

  • Full onboarding, tools training, and guidance from experienced data professionals.

  • The chance to work on live projects that make a real difference.

  • An inclusive, innovation-driven culture that encourages learning and growth.

  • Competitive salary, excellent benefits, and long-term career opportunities.

    Ready to kick-start your career in data analytics?
    Apply today and begin your journey into the world of data-driven decision-making

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.