Analyst, EMEA Forecasting

CBRE UK; Greater London; On-site; GBP 55,000 - 75,000; Full time

Job summary

CBRE is seeking an Analyst for EMEA Forecasting in London to join a small team of economists and quants. You will develop quarterly commercial real estate forecasts, translate model outputs into clear narratives, and contribute to AI-enabled forecasting infrastructure.

You will work closely with CBRE’s research and data science groups, presenting insights to internal stakeholders and clients. A strong quantitative background and communication skills are essential.

Qualifications

• A degree in economics, data science, statistics, finance, or a related quantitative field - at undergraduate or postgraduate level; PhD candidates with commercial experience are encouraged to apply
• Solid grounding in econometrics or quantitative modelling, you understand how to build, validate, and interpret models
• Proficiency in Python is expected; experience with statistical packages such as EViews, Stata or R is a plus, and familiarity with SQL is welcome
• A genuine appetite for AI and machine learning - you follow development, have experimented with modern tools, and are excited about applying them to real-world economic and real estate problems
• Prior exposure to property research, investment management, banking, or consultancy is valued
• Strong written and verbal communication skills

Responsibilities

• Drive quarterly commercial real estate forecasts and contribute to ongoing model improvement, bringing both quantitative rigor and informed views on market trends and emerging considerations
• Author regular economic and property market commentary, translating forward-looking model outputs into clear, insight-driven narratives for our audiences
• Help develop views and forecasts across alternative real estate sectors, expanding the team’s analytical coverage and deepening market intelligence
• Build and maintain relationships with sector specialists and research teams across CBRE, incorporating on-ground sentiment and market intelligence into quantitative frameworks
• Present forecasting outputs to internal stakeholders and external clients, communicating complex analysis with confidence and clarity
• Collaborate closely with economists and data scientists on R&D projects, model innovation, and the integration of AI and data science techniques into the team’s forecasting infrastructure

Skills

Python

Econometrics

Quantitative modelling

Communication

SQL

Education

Quantitative degree (economics, data science, statistics, finance)

Tools

SQL

Stata

R

EViews

Job description

Analyst, EMEA Forecasting

Location: London, UK

CBRE is the world’s leading commercial real estate services firm with offices located around the globe. The company’s core services include property sales, leasing and management, facilities and project management, investment management and research and consulting.

The Global Forecasting team builds the next generation of real estate intelligence focusing on forward‑looking indicators of real estate performance. This is an exciting role sitting at the crossroads of applied econometrics, data science, and AI - all anchored in the most exciting asset classes in the world.

You’ll join a small, high‑impact team of economists/quants within CBRE’s Global forecasting group. The team produces forward‑looking models that drive CBRE’s subscription intelligence platform - used by CBRE internal stakeholders, top‑tier investors and occupiers to make real estate decisions. We expect you to be able to talk and write coherently on economic matters within the context of commercial real estate.

What you will be doing

• Drive quarterly commercial real estate forecasts and contribute to ongoing model improvement, bringing both quantitative rigor and informed views on market trends and emerging considerations
• Author regular economic and property market commentary, translating forward‑looking model outputs into clear, insight‑driven narratives for our audiences
• Help develop views and forecasts across alternative real estate sectors, expanding the team’s analytical coverage and deepening market intelligence
• Build and maintain relationships with sector specialists and research teams across CBRE, incorporating on‑the‑ground sentiment and market intelligence into quantitative frameworks
• Present forecasting outputs to internal stakeholders and external clients, communicating complex analysis with confidence and clarity
• Collaborate closely with economists and data scientists on R&D projects, model innovation, and the integration of AI and data science techniques into the team’s forecasting infrastructure

What you will need to apply

• A degree in economics, data science, statistics, finance, or a related quantitative field - at undergraduate or postgraduate level; PhD candidates with commercial experience are encouraged to apply
• Solid grounding in econometrics or quantitative modelling, whether built in academia or industry - you understand how to build, validate, and interpret models, not just run them
• Proficiency in Python is expected; experience with statistical packages such as EViews, Stata or R is a plus, and familiarity with SQL is welcome
• A genuine appetite for AI and machine learning - you follow development, have experimented with modern tools, and are excited about applying them to real‑world economic and real estate problems
• Prior exposure to property research, investment management, banking, or consultancy is valued
• Strong written and verbal communication skills

Why CBRE

When you join CBRE, you become part of the global leader in commercial real estate services and investment that helps businesses and people thrive. We are dynamic problem solvers and forward‑thinking professionals who create significant impact. Our collaborative culture is built on our shared values - respect, integrity, service and excellence - and we value the diverse perspectives, backgrounds and skillsets of our people. At CBRE, you have the opportunity to chart your own course and realize your potential. We welcome all applicants.

Applicant AI Use Disclosure

We value human interaction to understand each candidate’s unique experience, skills and aspirations. We do not use artificial intelligence (AI) tools to make hiring decisions, and we ask that candidates disclose any use of AI in the application and interview process.