Information Systems Data Analyst

Blackburn
3 weeks ago
Applications closed

Related Jobs

View all jobs

HR Data Analytics - Asset Manager

Data Analyst

Senior Data Analyst

Financial Data Analyst

Data Analyst, London Geolytix Geolytix

Data Architect, Technology

Information Systems Data Analyst

Salary £31,456 to £35,403 gross per annum

37hrs Full Time

Generous staff benefits

You'll have access to a wide range of benefits and support, including, but not limited to: 

Employee Assistance Programme with a 24/7/365 helpline for advice and support 
Regular Staff Physical Activity Sessions and reduced-price gym membership 
Cycle to Work Scheme 
Family-friendly policies 
Free eye tests and contribution to VDU-use-only glasses 
Several food outlets with a variety of menu choices 
A full range of discounted professional Hair & Beauty services provided by the Academy Salon 
Professional bakery offering a variety of fresh breads, cakes, and ready meals. 

In this role you will play an active role in the development of the Information Systems and Business Intelligence Team services and project-manage the introduction of newly introduced systems throughout the entire project life cycle.

You will also be working with the Information Systems and Business Intelligence Manager to develop ebs Ontrack/Central and assist in the delivery of training for key college staff for all Systems and Reporting requirements. 

You will provide outstanding systems support, which meets the needs of internal stakeholders and supports the team in meeting their service standards. 

What we are looking for:

You should have a UK or ENIC recognised degree in a relevant subject or equivalent vocational qualification. You must have competency in the use of SQL Server Reporting Services and SQL Server Management Studio and recent knowledge and experience of SQL scripting.

You will have excellent IT skills and are highly proficient in the use of MS Office suite and experience of working with complex relational databases.

You must have qualification certificates that confirm you have achieved a minimum of level 2 in English and Maths.

Our College has nearly 700 people employed in a vast range of roles and feels more like a community than a workplace, and this sense of collaboration is just one of the benefits of working here. We strive to make our employee community a welcoming, caring, and enthusiastic one, fuelling ambition with opportunities and support to help us all achieve our personal and professional goals.

Please press APPLY and we shall send you full details.

Close date 13/3/25

Get the latest insights and jobs direct. Sign up for our newsletter.

By subscribing you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Tips for Staying Inspired: How Machine Learning Pros Fuel Creativity and Innovation

Machine learning (ML) continues to reshape industries—from personalised e-commerce recommendations and autonomous vehicles to advanced healthcare diagnostics and predictive maintenance in manufacturing. Yet behind every revolutionary model lies a challenging and sometimes repetitive process: data cleaning, hyperparameter tuning, infrastructure management, stakeholder communications, and constant performance monitoring. It’s no wonder many ML professionals can experience creative fatigue or get stuck in the daily grind. So, how do machine learning experts keep their spark alive and continually generate fresh ideas? Below, you’ll find ten actionable strategies that successful ML engineers, data scientists, and research scientists use to stay innovative and push boundaries. Whether you’re an experienced practitioner or just breaking into the field, these tips can help you fuel creativity and discover new angles for solving complex problems.

Top 10 Machine Learning Career Myths Debunked: Key Facts for Aspiring Professionals

Machine learning (ML) has become one of the hottest fields in technology—touching everything from recommendation engines and self-driving cars to language translation and healthcare diagnostics. The immense potential of ML, combined with attractive compensation packages and high-profile success stories, has spurred countless professionals and students to explore this career path. Yet, despite the boom in demand and innovation, machine learning is not exempt from myths and misconceptions. At MachineLearningJobs.co.uk, we’ve had front-row seats to the real-life career journeys and hiring needs in this field. We see, time and again, that outdated assumptions—like needing a PhD from a top university or that ML is purely about deep neural networks—can mislead new entrants and even deter seasoned professionals from making a successful transition. If you’re curious about a career in machine learning or looking to take your existing ML expertise to the next level, this article is for you. Below, we debunk 10 of the most persistent myths about machine learning careers and offer a clear-eyed view of the essential skills, opportunities, and realistic paths forward. By the end, you’ll be better equipped to make informed decisions about your future in this dynamic and rewarding domain.

Global vs. Local: Comparing the UK Machine Learning Job Market to International Landscapes

How to evaluate opportunities, salaries, and work culture in machine learning across the UK, the US, Europe, and Asia Machine learning (ML) has rapidly transcended the research labs of academia to become a foundational pillar of modern technology. From recommendation engines and autonomous vehicles to fraud detection and personalised healthcare, machine learning techniques are increasingly ubiquitous, transforming how organisations operate. This surge in applications has fuelled an extraordinary global demand for ML professionals—data scientists, ML engineers, research scientists, and more. In this article, we’ll examine how the UK machine learning job market compares to prominent international hubs, including the United States, Europe, and Asia. We’ll explore hiring trends, salary ranges, workplace cultures, and the nuances of remote and overseas roles. Whether you’re a fresh graduate aiming to break into the field, a software engineer with an ML specialisation, or a seasoned professional seeking your next challenge, understanding the global ML landscape is essential for making an informed career move. By the end of this overview, you’ll be equipped with insights into which regions offer the best blend of salaries, work-life balance, and cutting-edge projects—plus practical tips on how to succeed in a domain that’s constantly evolving. Let’s dive in.