Local Gov't Housing Data Analyst Temp: West London

Adecco
London
1 month ago
Applications closed

Related Jobs

View all jobs

Performance & Data Analyst

Data Engineer

Data Analyst

Junior IT Support Engineer & Data Analyst

Data Analyst

Data Analyst - Maritime

An exciting opportunity has emerged for a Data Analyst to join the homelessness department at one of Adecco's leading Local Government clients in a temporary role for the next six months, with potential extension beyond this. This is a full time role (36 hours per week, Monday to Friday) working hybridly from our client's West London office 2 days each week, and previous experience of working within a local government housing department would be highly desirable.

The role will be reporting directly into the Assistant Director Housing Demand/ Programme Director, and the work is analysing data in the service to provide management insight and is core to financial control within housing demand. It will assist in providing accurate budgetary forecasting and analysis of their cohort in temporary accommodation, and those households presenting as homeless, and will enable the effective prioritisation of project work to manage spend within the directorate as well as improve outcomes for residents.

There are data quality issues within our client's systems, so this role would need to actively understand the accuracy of the data, cross-compare sources and potentially do other investigatory work to provide a view about reliability, as well as identify ways to data cleanse and resolve some of the issues identified.

Other key elements of this role include:

  • Designing, developing, testing and debugging SQL Server Integration...

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.

Products

Where to Advertise Data Science Jobs in the UK (2026 Guide)

Advertising data science jobs in the UK requires a different approach to most technical hiring. Data science spans a broad and often misunderstood spectrum — from statistical modelling and experimental design through to machine learning engineering, product analytics and AI research. The strongest candidates identify firmly with specific subdisciplines and are frustrated by adverts that conflate data scientist with data analyst, business intelligence developer or machine learning engineer. General job boards produce high application volumes for data roles but consistently fail to match specialist data science profiles with the right opportunities. This guide, published by DataScienceJobs.co.uk, covers where to advertise data science roles in the UK in 2026, how the main platforms compare, what employers should expect to pay, and what the data says about hiring across different role types.

Jobs

New Data Science Employers to Watch in 2026: UK and International Companies Leading Analytics and AI Innovation

Data science has emerged as one of the most transformative forces across industries, turning raw information into actionable insights, predictive models, and AI-powered solutions. In 2026, the UK is witnessing a surge in organisations where data science is not just a support function but the core of their products and services. For professionals exploring opportunities on www.DataScience-Jobs.co.uk , identifying these employers early can provide a competitive advantage in a market with high demand for advanced analytics and machine learning expertise. This article highlights new and high-growth data science employers to watch in 2026, focusing on UK startups, scale-ups, and global firms expanding their data science operations locally. All of the companies included have recently raised investment, won high-profile contracts, or significantly scaled their analytics teams.

Careers

How Many Data Science Tools Do You Need to Know to Get a Data Science Job?

If you’re trying to break into data science — or progress your career — it can feel like you are drowning in names: Python, R, TensorFlow, PyTorch, SQL, Spark, AWS, Scikit-learn, Jupyter, Tableau, Power BI…the list just keeps going. With every job advert listing a different combination of tools, many applicants fall into a trap: they try to learn everything. The result? Long tool lists that sound impressive — but little depth to back them up. Here’s the straight-talk version most hiring managers won’t explicitly tell you: 👉 You don’t need to know every data science tool to get hired. 👉 You need to know the right ones — deeply — and know how to use them to solve real problems. Tools matter, but only in service of outcomes. So how many data science tools do you actually need to know to get a job? For most job seekers, the answer is not “27” — it’s more like 8–12, thoughtfully chosen and well understood. This guide explains what employers really value, which tools are core, which are role-specific, and how to focus your toolbox so your CV and interviews shine.

🍪 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.