Capital Fund Management (CFM) is a successful alternative investment manager and a pioneer in the field of quantitative trading applied to capital markets across the globe. Our methodology relies on statistically robust analysis of terabytes of financial data for asset allocation, trading decisions and automated order execution.
CFM is an appealing career destination for highly-talented and passionate PhD’s, IT engineers and experts from around the world. Our people can rely on original theoretical insight accumulated over 25 years of market experience, as well as cutting-edge technology for our systematic trading.
These fundamentals allow us to foster the creation of exciting opportunities and state-of-the-art trading strategies.
Our people’s diversity and dedication contribute to CFM’s unique culture of research, innovation and achievement.
The position involves applied research in financial time series in order to detect and exploit any robust statistical pattern. The aim is to build new statistical arbitrage strategies, to supplement those already devised and implemented by CFM. You will be working in a team of 55 researchers in close collaboration with software engineers.
The work will consist in developing new statistical tools, exploiting some of the recent theoretical models developed, carefully backtesting the robustness through data analysis and implementing them in practice.
The candidate should be both creative, in order to imagine new ways of detecting hidden statistical patterns, and rigorous.
Although a high interest in finance is crucial, no prior knowledge in the field is needed.
Founded in 1991, CFM is currently one of the world's leaders in alternative investment management. We invite you to join an extremely dynamic and motivating company in a pleasant space in the heart of Paris. Our compensation package is very attractive, offering a substantial bonus (that can range from 50% - 150%+ of fixed salary, depending on global and individual performance).
The company is regulated by the AMF, the SEC and the CFTC, with assets under management of $10 billion.
- PhD in experimental or theoretical science (life science, mathematics, physics, statistics etc.)
- Post PhD experience (academic or private sector research), 5+ years experience would be appreciated,
- Taste for exploration of new data sets, modelling and practical implementations in simulation environments,
- Programming skills in Python,C++ or R,
- Adaptable and rigorous, capable of working in a quickly evolving environment,
- Strong teamwork and communication skills.
If you are interested and feel that you are suited to the role, please send your PDF résumé and a cover letter on: