Automation Data Analyst

Risley, Warrington
11 months ago
Applications closed

Related Jobs

View all jobs

Data Science and Innovation Manager

Senior Lead Analyst - Data Science_ AI/ML & Gen AI

Actuarial Data Scientist

Data Scientist

Data Scientist within Asset & Wealth Management (Senior Associate)

Data Scientist within Asset & Wealth Management (Senior Associate)

Our client, a leading engineering and maintenance provider in the energy sector, is seeking a highly skilled and motivated Automation Data Analyst to join their team in Warrington. Our client supports the efficiency of assets across various markets, enhancing availability and reducing maintenance costs.
Key Responsibilities:

Collect, process, and analyse large datasets to identify trends, patterns, and insights
Generate reports, dashboards, and visualisations using PowerBi to communicate findings to stakeholders
Collaborate with various departments to understand their data needs and provide data-driven solutions
Collaborate with global teams to align with group standards and implement global process changes locally
Improve and maintain data interfaces to ensure data quality and accessibility
Develop and implement data models and algorithms to support business objectives
Monitor and evaluate the performance of data-driven initiatives and provide recommendations for improvement
Stay up-to-date with industry trends and best practices in data analysis and business intelligence
Develop comprehensive documentation on data models and flowsJob Requirements:

Experience in a Data Analyst or similar role within an industrial environment
Bachelor's degree or equivalent in data science, statistics, computer science, or a related field
Proficiency in data analysis tools and software, such as PowerBi, SQL, and Excel
Strong analytical and problem-solving skills
Excellent communication and presentation skills
Ability to work independently and as part of a team
Attention to detail and a commitment to data accuracy and integrity
Experience working with multiple disciplines of teams within an industrial business or environment
Knowledge of programming languages such as Python or R
Familiarity with machine learning algorithms and predictive modellingBenefits:

Permanent role with a leading engineering and maintenance provider
Opportunity to work on a variety of projects across multiple sectors
Professional development and training opportunities
Supportive and collaborative work environment
Employee benefits package
If you are an experienced Data Analyst looking for a new opportunity to further develop your career within the energy and automation sectors, we would love to hear from you. Apply now to join our client's dynamic and talented team in Warrington

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.