Data Support & Tech Author

Wembdon
11 months ago
Applications closed

Related Jobs

View all jobs

Data Engineer

Data Engineer

Data Engineer

Principal Data Scientist London, United Kingdom

Senior Data Analyst

Data Engineer (KTP Associate Position) - Salford

Data Support & Tech Author- (phone number removed)

Shift Times: Flexible working available - 37HPW
Pay Rate: £270 - per day
Location: TA6 7LQ, Bridgewater

Job Purpose / Overview

An opportunity has arisen for a Data Analyst to join the Maintenance Team within the site Comm-Ops Directorate. Based at Hinkley Point C you will be part of an expanding multidiscipline team responsible for planning and executing maintenance on equipment that will be required to build, commission and operate Hinkley Point C Power Station. The role will primarily be focused on Data extraction and analysis. The successful candidate will be responsible for populating the Asset Register along with associated attributes within HPC's EAM tool.

Key Responsibilities:

Maintain the accuracy of the Asset Register in the Enterprise Asset Management (EAM) Tool
Provide a legible meaningful description for the Assets
Populate equipment type against Assets
Maintain location data against the Asset register
Populate Divisions against Assets. Maintain the divisions data.
Populate Systems against Assets. Maintain the systems data.
To succeed you will need

Strong attention to detail when working with data to make accurate conclusions and predictions
Strong verbal and written communication skills to effectively share findings with shareholders
A solid understanding of data sources, data organisation and storage
Strong IT skills, Excel, Word, Power Point
Knowledge of data analysis techniques
Experience of working with large data sets
Knowledge of Power Bi
Qualifications & Experience

A degree in a relevant discipline
Good written and verbal communication skills

Apply now and a member of the team will be in touch

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.

What Hiring Managers Look for First in Machine Learning Job Applications (UK Guide)

Whether you’re applying for machine learning engineer, applied scientist, research scientist, ML Ops or data scientist roles, hiring managers scan applications quickly — often making decisions before they’ve read beyond the top third of your CV. In the competitive UK market, it’s not enough to list skills. You must send clear signals of relevance, delivery, impact, reasoning and readiness for production — and do it within the first few lines of your CV or portfolio. This guide walks you through exactly what hiring managers look for first in machine learning applications, how they evaluate CVs and portfolios, and what you can do to improve your chances of getting shortlisted at every stage — from your CV and LinkedIn profile to your cover letter and project portfolio.

MLOps Jobs in the UK: The Complete Career Guide for Machine Learning Professionals

Machine learning has moved from experimentation to production at scale. As a result, MLOps jobs have become some of the most in-demand and best-paid roles in the UK tech market. For job seekers with experience in machine learning, data science, software engineering or cloud infrastructure, MLOps represents a powerful career pivot or progression. This guide is designed to help you understand what MLOps roles involve, which skills employers are hiring for, how to transition into MLOps, salary expectations in the UK, and how to land your next role using specialist platforms like MachineLearningJobs.co.uk.

The Skills Gap in Machine Learning Jobs: What Universities Aren’t Teaching

Machine learning has moved from academic research into the core of modern business. From recommendation engines and fraud detection to medical imaging, autonomous systems and language models, machine learning now underpins many of the UK’s most critical technologies. Universities have responded quickly. Machine learning modules are now standard in computer science degrees, specialist MSc programmes have proliferated, and online courses promise to fast-track careers in the field. And yet, despite this growth in education, UK employers consistently report the same problem: Many candidates with machine learning qualifications are not job-ready. Roles remain open for months. Interview processes filter out large numbers of applicants. Graduates with strong theoretical knowledge struggle when faced with practical tasks. The issue is not intelligence or effort. It is a persistent skills gap between university-level machine learning education and real-world machine learning jobs. This article explores that gap in depth: what universities teach well, what they routinely miss, why the gap exists, what employers actually want, and how jobseekers can bridge the divide to build successful careers in machine learning.