Data Analyst, UK

Shields
Purfleet-on-Thames
1 week ago
Applications closed

Related Jobs

View all jobs

Data Analyst

Data Analyst Career Pathway for Beginners

Data Analyst Career Pathway for Beginners

Data Analyst Placement Programme

Data Analyst - FTC

Data Analyst

Job Title – Data Analyst
Job Focus – Software
Reports To – Product Manager
Location – Purfleet, Essex
Region of Work – Technical Team

Key Responsibilities
  • Develop, implement and manage efficient ETL (Extract/Transform/Load) processes
  • Manage existing data sources and investigate and develop new sources
  • Cleaning and collating of data from our MarketPlace platform
  • Produce Analytics for our products, services and MarketPlace platform. Connecting the dots between relevant platforms and data feeds
  • Automation of alerts and reporting to support the day to day business, presenting our biggest risks and weakness trends
  • Investigate tools and best practices to store, structure and analyse data for MarketPlace
  • Actively share knowledge and document defined processes
  • Provide an overall increased level of automation within data systems and software platform
  • Develop and support the implementation of data quality improvement efforts
Required
  • Advanced analytical knowledge of data
  • Proficiency in statistics, data analysis, and research methods
  • Excellent knowledge of relevant programming languages (SQL, Python, R etc)
  • Experience with Power BI and other data visualisation tools (desirable)
  • Experience with cloud platforms – Azure
  • Experience in interfacing with APIs
  • Microsoft Office platform including Power BI
  • Understanding of or experience with machine learning
  • Telecoms Industry background
What does Shields give you?
  • Company bonus scheme
  • Company Phantom Share Scheme
  • 25 days holiday, bank holidays and your birthday off
  • Monday – Friday 8.30am-5pm
  • On-site parking

We are committed to building an inclusive culture of belonging that not only embraces the diversity of our people but also reflects the diversity of the communities in which we work and the customers we serve. We know that the happiest and highest performing teams include people with diverse perspectives and ways of solving problems so we strive to attract and retain talent from all backgrounds and create workplaces where everyone feels empowered to bring their full, authentic selves to work.

Shields is an Equal Opportunity employer. All qualified applicants will receive consideration for employment without regard to race, religion, sex including sexual orientation and gender identity, national origin, disability, protected veteran status, or any other characteristic protected by applicable national or local law.

Since 1979, Shields Environmental has partnered with the world’s leading telecommunications companies to provide innovative multi-vendor spares management solutions (incl. Repair), specialist logistics and Field services, reuse, extended life and recycling solutions within a fully integrated environmental and compliance risk management program.

Shields works hard to build a reputation for entrepreneurial spirit, innovation, unparalleled knowledge of the industry, environmental excellence and customer service. The core of this service is our talented employees.


#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.

Education

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.

Careers Jobs

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

Are you considering a career change into machine learning in your 30s, 40s or 50s? You’re not alone. In the UK, organisations across industries such as finance, healthcare, retail, government & technology are investing in machine learning to improve decisions, automate processes & unlock new insights. But with all the hype, it can be hard to tell which roles are real job opportunities and which are just buzzwords. This article gives you a practical, UK-focused reality check: which machine learning roles truly exist, what skills employers really hire for, how long retraining realistically takes, how to position your experience and whether age matters in your favour or not. Whether you come from analytics, engineering, operations, research, compliance or business strategy, there is a credible route into machine learning if you approach it strategically.

Jobs

How to Write a Machine Learning Job Ad That Attracts the Right People

Machine learning now sits at the heart of many UK organisations, powering everything from recommendation engines and fraud detection to forecasting, automation and decision support. As adoption grows, so does demand for skilled machine learning professionals. Yet many employers struggle to attract the right candidates. Machine learning job adverts often generate high volumes of applications, but few applicants have the blend of modelling skill, engineering awareness and real-world experience the role actually requires. Meanwhile, strong machine learning engineers and scientists quietly avoid adverts that feel vague, inflated or confused. In most cases, the issue is not the talent market — it is the job advert itself. Machine learning professionals are analytical, technically rigorous and highly selective. A poorly written job ad signals unclear expectations and low ML maturity. A well-written one signals credibility, focus and a serious approach to applied machine learning. This guide explains how to write a machine learning job ad that attracts the right people, improves applicant quality and strengthens your employer brand.

🍪 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.