Quant jobs / Capital Fund Management (CFM)

Quantitative Researcher – Economics

A quantitative research role at CFM focused on turning economic and alternative datasets into trading signals. It sits among more than 100 researchers and works with data and software engineers.

What you’d work on

Our reading of the posting: what a new hire in this role would most likely spend their first months on.

Form investment hypotheses from fundamental and economic data
Test them with backtests and statistical analysis
Assess new datasets (traditional and alternative) for useful information
Relate new features to known economic quantities
Work with engineers to put signals into production

What they ask for

Required

PhD in economics
Post-PhD research experience, academic or private
Applied ML and econometrics on large datasets
Python
Rigorous testing of ideas
Teamwork and communication

Education: PhD in economics
Experience: Post-PhD academic or private-sector research experience
Languages and tools: Python

How to prepare

Replicate a published return-predictability result with a modern dataset and check how much holds out of sample
Build a signal from an economic or alternative data source and backtest it with costs
Revise econometrics: panel regressions, time series, identification and regularised methods
Practise machine learning on large tabular data with careful cross-validation
Prepare a short presentation explaining the economic story behind a signal

What to study

The Quantitative Researcher roadmap sets out the stages for this kind of role, with free resources for each.

Open the roadmap

Apply

Read the full posting on Capital Fund Management (CFM)’s site before applying: requirements, location and pay can change after we check them.

View the posting on Capital Fund Management (CFM)’s site ↗

SelfMadeQuant wrote this summary from the employer’s public posting, last checked 6 November 2026. SelfMadeQuant isn’t affiliated with Capital Fund Management (CFM) and doesn’t handle applications.