CMMS & Data Analyst

London
8 months ago
Applications closed

CMMS & Data Analyst

Location: Remote (occasional monthly visit to St Albans)

About the Role: As a CBRE Data Analyst, you will perform basic analysis to ensure that recommendations and business conclusions are backed by thorough data research and findings.

This job is part of the Data Science & Analytics job function. They are responsible for reviewing data that supports improving effectiveness and predicting outcomes to develop business intelligence.

What You'll Do:

Coordinate data aggregation and curate reports using existing business intelligence and reporting applications.
Perform ad-hoc, strategic review of structured and unstructured data, reflecting global real estate markets and the operations of real estate assets.
Assist with developing data structures and pipelines to organize, collect, cleanse, and standardize information to generate insights.
Define basic data requirements and gather information using judgment and statistical tests.
Use programming and evaluation tools, including open-source programs to plan models and extract insights.
Apply modeling and optimization methods to improve business performance.
Develop ad-hoc reporting based on the review of existing data sources.
Exhibit rigor, judgment, and ability to present a detailed 'data story' to a business line.
Confirm the quality and integrity of existing data sources.
Collaborate with the agile development team to provide recommendations and communications on enhancing existing or new processes and programs.
Have some knowledge of standard principles with limited practical experience in applying them.
Lead by example and model behaviors that are consistent with CBRE RISE values.
Impact the quality of own work.
Work within standardized procedures and practices to achieve objectives and meet deadlines.
Exchange straightforward information, ask questions, and check for understanding.What You'll Need:

Bachelor's Degree preferred with up to 3 years of relevant experience. In lieu of a degree, a combination of experience and education will be considered. MCSE and CNE Certification preferred.
Ability to use existing procedures to solve standard problems.
Experience with analyzing information and standard practices to make judgments.
In-depth knowledge of Microsoft Office products. Examples include Word, Excel, Outlook, etc.
Organizational skills with a strong inquisitive mindset

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.

New Machine Learning Employers to Watch in 2026: UK and Global Companies Driving ML Innovation

Machine learning (ML) has transitioned from a specialised field into a core business capability. In 2026, organisations across healthcare, finance, robotics, autonomous systems, natural language processing, and analytics are expanding their machine learning teams to build scalable intelligent products and services. For professionals exploring opportunities on www.MachineLearningJobs.co.uk , understanding the companies that are scaling, winning investment, or securing high‑impact contracts is crucial. This article highlights the new and high‑growth machine learning employers to watch in 2026, focusing on UK innovators, international firms with significant UK presence, and global platforms investing in machine learning talent locally.

How Many Machine Learning Tools Do You Need to Know to Get a Machine Learning Job?

Machine learning is one of the most exciting and rapidly growing areas of tech. But for job seekers it can also feel like a maze of tools, frameworks and platforms. One job advert wants TensorFlow and Keras. Another mentions PyTorch, scikit-learn and Spark. A third lists Mlflow, Docker, Kubernetes and more. With so many names out there, it’s easy to fall into the trap of thinking you must learn everything just to be competitive. Here’s the honest truth most machine learning hiring managers won’t say out loud: 👉 They don’t hire you because you know every tool. They hire you because you can solve real problems with the tools you know. Tools are important — no doubt — but context, judgement and outcomes matter far more. So how many machine learning tools do you actually need to know to get a job? For most job seekers, the real number is far smaller than you think — and more logically grouped. This guide breaks down exactly what employers expect, which tools are core, which are role-specific, and how to structure your learning for real career results.

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.