Trainee Data Analyst

Small Heath
10 months ago
Applications closed

Related Jobs

View all jobs

AI/Data Scientist

Senior Data Scientist

Senior Machine Learning Engineer

Graduate Machine Learning and AI Engineer

Senior Machine Learning Engineer

Machine Learning Engineer (Manager)

Join a leading IT firm as a Trainee Data Analyst and embark on a promising career path in data analysis. This entry-level role is ideal for recent graduates or individuals transitioning into the IT sector, offering a robust platform to develop analytical skills and contribute to impactful projects.

Responsibilities:

  • Support the collection and processing of complex data sets from varied sources to aid in decision-making processes.

  • Work closely with senior analysts to manage and optimise databases and analytical systems.

  • Utilise statistical methods to analyse data and generate useful business reports.

  • Participate in the design and implementation of data gathering and data processing systems.

  • Interpret data and collaborate with the IT team to enhance business operations through data-driven insights.

  • Prepare reports and visualisations to communicate findings to internal and external stakeholders.

    Requirements:

  • Holds a Bachelor’s degree in Data Science, Computer Science, Information Technology, or related fields.

  • Demonstrates strong analytical skills and precision in handling and interpreting data.

  • Familiarity with statistical software and tools (e.g., Excel, SPSS, SAS) and basic knowledge of SQL and data visualisation tools like Tableau.

  • Possesses excellent communication skills, capable of explaining complex data in a straightforward way.

  • Shows initiative, ability to work independently, and commitment to personal and professional growth.

    Offering:

  • A structured training program designed to build expertise in data analysis.

  • Career progression opportunities in a thriving and innovative sector.

  • Exposure to advanced technologies and methodologies in data handling.

  • A supportive and diverse team environment that fosters professional development.

    This position represents a fantastic opportunity for individuals eager to develop as data analysts within the rapidly evolving IT industry. Our client values diversity and encourages applications from all qualified candidates, regardless of background

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.

Careers

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.

Jobs

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.

Education

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.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.