Graduate Data Scientist / Junior Analyst in London

Energy Jobline ZR
City of London
3 months ago
Applications closed

Related Jobs

View all jobs

Junior / Graduate Data Scientist

Junior / Graduate Data Scientist

Data Science Trainee

Data Science Trainee

Data Science Trainee

Data Science Trainee

Energy Jobline is the largest and fastest growing global Energy Job Board and Energy Hub. We have an audience reach of over 7 million energy professionals, 400,000+ monthly advertised global energy and engineering jobs, and work with the leading energy companies worldwide.


We focus on the Oil & Gas, Renewables, Engineering, Power, and Nuclear markets as well as emerging technologies in EV, Battery, and Fusion. We are committed to ensuring that we offer the most exciting career opportunities from around the world for our jobseekers.


Job Description

Graduate Data Scientist / Junior Analyst


Kickstart your career in data science by joining a team that’s redefining how performance insights are measured and delivered. This London-based analytics business is seeking a Graduate Data Scientist / Junior Analyst to support its leading leaderboard and intelligence platform.


Company overview: This fast-growing insights and analytics organisation delivers data-led solutions that help clients evaluate performance and make informed strategic decisions. Combining technology and analytical expertise, the company’s products are trusted by organisations seeking evidence-based intelligence and benchmarking.


Job overview: As a Graduate Data Scientist / Junior Analyst, you’ll work closely with the analytics and development teams to collect, process and interpret large datasets. You’ll be integral to improving the company’s flagship leaderboard product, helping refine algorithms and provide meaningful insights to clients.


Here’s what you'll be doing:

  • Gathering, cleaning and analysing data for the leaderboard analytics platform
  • Building dashboards, reports and visualisations to communicate key metrics
  • Supporting data modelling and performance tracking processes
  • Collaborating with developers to enhance the accuracy and usability of analytical outputs
  • Researching emerging data science trends and recommending improvements

Here are the skills you'll need:

  • Degree in Data Science, Statistics, Computer Science, Economics or related field
  • Competence in Python, R or SQL for data manipulation and analysis
  • Experience using data visualisation tools (Power BI, Tableau or similar)
  • Strong numerical and analytical ability with good attention to detail
  • Effective communicator with enthusiasm for data-driven problem-solving

Work permissions

You must have the right to work in the United Kingdom. Visa sponsorship is not available at this time.


Here are the benefits of this job:

  • £25,000–£28,000 pro rata salary (6-month with potential to become permanent)
  • Remote-first role with one monthly visit to the London office
  • Mentorship from experienced data professionals
  • Opportunity to work on a high-profile, real-world analytics product
  • Career growth potential within data science or analytics consultancy

A role as a Graduate Data Scientist / Junior Analyst offers a strong foundation for a long-term career in data analytics. With demand for data professionals continuing to grow, this opportunity provides practical experience in statistical analysis, product development and data-driven decision-making.


If you are interested in applying for this job please press the Apply Button and follow the application process. Energy Jobline wishes you the very best of luck in your next career move.


#J-18808-Ljbffr

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.