Housing Revenue Systems & Data Analyst

Camden Town
1 week ago
Create job alert

Housing Revenue Systems & Data Analyst (Temporary)
Location: 5 Pancras Square (Agile/Hybrid Working)
Contract: Temporary | Rate: £30.02 Ltd / £23.00 PAYE per hour
Directorate: Supporting Communities – Housing Services
Are you an experienced systems and data professional with a passion for improving housing services? We're working on behalf of a local authority to recruit a Housing Revenue Systems & Data Analyst on a temporary basis, playing a pivotal role within the Rent Accounting Team.
This is a fantastic opportunity to contribute to a data-driven, resident-focused council where your expertise will have a real impact.
About the Role:
You’ll be responsible for managing and enhancing housing finance systems, improving data quality, and ensuring statutory compliance. The role combines technical system oversight, reporting, and strategic support across all rent-related activities.
Key Responsibilities:
Systems & Compliance:

Maintain and configure systems like Northgate NEC
Act as a gatekeeper for finance-related system changes
Lead on user acceptance testing and rollout
Ensure compliance with statutory rent processes and communicationBusiness Intelligence & Reporting:

Develop reports on arrears, recovery, income and service charges
Support rent-setting and forecasting activities
Use SQL, QlikSense, and SAP BusinessObjects to produce actionable insights
Lead on data quality assuranceOperational Support:

Oversee rent reconciliation and transaction matching
Manage statutory rent statements and returns
Handle ad hoc data requests as neededStrategic Development:

Contribute to wider council IT transformation projects
Map business processes and support system integration
Liaise with Corporate Finance to ensure financial gatekeepingAbout You:
The ideal candidate will bring:

Strong experience with housing and finance systems (ideally Northgate NEC)
Advanced data skills, including SQL and performance reporting
Knowledge of housing policy, rent legislation, and financial compliance
A collaborative mindset with the ability to work across teams and services
Experience with ITIL, social housing, or CCAB study is advantageousWhy Apply?

Flexible hybrid working arrangements
High-impact, rewarding work in public service
Opportunity to collaborate on transformation projectsInterested in making a meaningful impact through housing systems and data?
If you are interested in this position and meet the above criteria, please send your CV now for consideration.
For more information, please contact George at Service Care Solutions on (phone number removed) or email (url removed)

Related Jobs

View all jobs

Interim Head of Data & Analytics

Founding Machine Learning Engineer

Machine Learning Engineer - FinTech

Data Analyst - Sustainability

Property Consultant - Stock Condition & EPC Specialist

Senior Data Analyst

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.

Rural-Remote Machine Learning Jobs: Finding Balance Beyond the Big Cities

Over the past decade, machine learning (ML) has transformed from a niche research domain into a pervasive technology underpinning everything from recommendation systems and voice assistants to financial forecasting and autonomous vehicles. Historically, the UK’s major tech hubs—particularly London—have been magnets for top ML talent and corporate headquarters. However, remote work has become mainstream, and many ML professionals are realising they can excel in their field while living far beyond the city limits. At MachineLearningJobs.co.uk, we’ve observed a growing interest in positions that allow for a rural lifestyle or a coastal environment, often reflected in search terms like “ML remote countryside” or “tech jobs by the sea.” This surge is no coincidence. Flexible work policies, better rural broadband, and the nature of machine learning tasks—much of which can be done through cloud platforms—are bringing new opportunities to those who wish to swap urban hustle for fresh air and scenic views. Whether you’re a data scientist, ML engineer, researcher, or product manager, a rural or seaside move could reinvigorate your work-life balance. In this article, we’ll unpack why rural-remote ML jobs are on the rise, how you can navigate the challenges of leaving the city, and what you need to do to thrive in a machine learning career beyond the M25. If you’ve dreamt of looking up from your laptop to rolling fields or ocean waves, keep reading—your rural ML role might be closer than you think.

Quantum-Enhanced Machine Learning—Propelling AI into the Next Frontier

Machine learning (ML) has revolutionised how we interpret data, build predictive models, and create intelligent applications. From recommendation engines and self-driving cars to advanced genomics and natural language processing, ML solutions are integral to nearly every corner of modern life. However, as data complexity and model size continue to skyrocket, the computational demands placed on ML systems grow in tandem—often pushing even high-performance classical computers to their limits. In recent years, quantum computing has emerged as a tantalising solution to these challenges. Unlike traditional digital systems, quantum computers exploit quantum mechanics—superposition and entanglement—to process information in ways that defy conventional logic. As these machines mature, they promise exponential speed-ups for certain tasks, potentially reshaping how we approach AI and data-intensive challenges. What does this mean for machine learning? Enter quantum-enhanced ML, a new frontier where quantum processors and classical ML frameworks unite to accelerate model training, tackle high-dimensional data, and solve complex optimisation tasks more efficiently. In this article, we will: Unpack the current state of machine learning, highlighting key bottlenecks. Provide a concise overview of quantum computing—why it’s radical and how it differs from classical technology. Examine potential breakthroughs in quantum-enhanced ML, including real-world use cases and technical approaches. Explore the roles and skill sets that will define this quantum-AI era, with guidance on how to prepare. Discuss the roadblocks (like hardware maturity and ethical concerns) and how they might be addressed in the years to come. If you’re a machine learning engineer, data scientist, or simply an AI enthusiast fascinated by the next wave of computational innovation, read on—quantum computing could become an integral part of your future toolkit, opening up job opportunities and reimagining what ML can achieve.

Machine Learning Jobs at Newly Funded UK Start-ups: Q3 2025 Investment Tracker

Machine learning (ML) has become the beating heart of modern tech innovation, powering breakthroughs in healthcare, finance, cybersecurity, robotics, and more. Across the United Kingdom, this surge in ML-driven solutions is fueling the success of countless start-ups—and spurring demand for talented machine learning engineers, data scientists, and related professionals. If you’re eager to join a high-growth ML company or simply want to keep tabs on the latest trends, this Q3 2025 Investment Tracker will guide you through the newly funded UK start-ups pushing the boundaries of ML. In this article, we’ll highlight key developments from Q3 2025, delve into the most promising newly funded ventures, and shed light on the machine learning roles they’re urgently seeking to fill. Plus, we’ll show you how to connect with these employers via MachineLearningJobs.co.uk, a dedicated platform for ML job seekers. Let’s dive in!