Entry Level Data Analyst

Farringdon
8 months ago
Applications closed

Related Jobs

View all jobs

Data Science Apprentice – Level 6 (Degree)

Data Science Apprentice – Level 6 (Degree)

2026 Apprentice - Digital (Data Science) - Belfast

Entry-Level Data Scientist — Sports Analytics

Pricing Data Scientist – Customer Insights (Hybrid)

BSc (Hons) Data Science

Are you passionate about data and ready to turn numbers into insights? Our client, a major name in IT and technology, is looking for an Entry Level Data Analyst to join their growing analytics team.

Key Responsibilities:

  • Collect, clean, and analyze data to support business decisions

  • Work on dashboards, visualizations, and reports

  • Identify trends and inconsistencies in datasets

  • Support automation and data processing initiatives

  • Translate business needs into data-driven insights

    Ideal Candidate:

  • Degree in Data Science, Mathematics, Statistics, or related field

  • Strong Excel and basic SQL skills (knowledge of Tableau or Power BI is a plus)

  • Detail-oriented with an analytical mindset

  • Excellent communicator, especially with non-technical teams

  • Curious, motivated, and eager to grow

    What You’ll Get:

  • Real-world project experience

  • Inclusive and collaborative work culture

  • Excellent growth opportunities and benefits

    Ready to build your career in data? Apply today

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.

Jobs Careers

AI Jobs for Career Switchers in Their 30s, 40s & 50s (UK Reality Check)

Changing career into artificial intelligence in your 30s, 40s or 50s is no longer unusual in the UK. It is happening quietly every day across fintech, healthcare, retail, manufacturing, government & professional services. But it is also surrounded by hype, fear & misinformation. This article is a realistic, UK-specific guide for career switchers who want the truth about AI jobs: what roles genuinely exist, what skills employers actually hire for, how long retraining really takes & whether age is a barrier (spoiler: not in the way people think). If you are considering a move into AI but want facts rather than Silicon Valley fantasy, this is for you.

Jobs

How to Write an AI Job Ad That Attracts the Right People

Artificial intelligence is now embedded across almost every sector of the UK economy. From fintech and healthcare to retail, defence and climate tech, organisations are competing for AI talent at an unprecedented pace. Yet despite the volume of AI job adverts online, many employers struggle to attract the right candidates. Roles are flooded with unsuitable applications, while highly capable AI professionals scroll past adverts that feel vague, inflated or disconnected from reality. In most cases, the issue isn’t a shortage of AI talent — it’s the quality of the job advert. Writing an effective AI job ad requires more care than traditional tech hiring. AI professionals are analytical, sceptical of hype and highly selective about where they apply. A poorly written advert doesn’t just fail to convert — it actively damages your credibility. This guide explains how to write an AI job ad that attracts the right people, filters out mismatches and positions your organisation as a serious employer in the AI space.

Education Jobs

Maths for AI Jobs: The Only Topics You Actually Need (& How to Learn Them)

If you are a software engineer, data scientist or analyst looking to move into AI or you are a UK undergraduate or postgraduate in computer science, maths, engineering or a related subject applying for AI roles, the maths can feel like the biggest barrier. Job descriptions say “strong maths” or “solid fundamentals” but rarely spell out what that means day to day. The good news is you do not need a full maths degree worth of theory to start applying. For most UK roles like Machine Learning Engineer, AI Engineer, Data Scientist, Applied Scientist, NLP Engineer or Computer Vision Engineer, the maths you actually use again & again is concentrated in a handful of topics: Linear algebra essentials Probability & statistics for uncertainty & evaluation Calculus essentials for gradients & backprop Optimisation basics for training & tuning A small amount of discrete maths for practical reasoning This guide turns vague requirements into a clear checklist, a 6-week learning plan & portfolio projects that prove you can translate maths into working code.

🍪 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.