Is CFM what you’re looking for?
We’re a global asset manager, founded in 1991 and a pioneer in the field of quantitative trading with assets under management of $10 billion. We are innovative, collaborative and believe in diversity with around 30 nationalities, across our five offices in Paris, New York, London, Tokyo and Sydney.

What can CFM offer you?
We create an environment for highly-talented and passionate PhDs, IT engineers and other recognised experts to explore new ideas and challenge assumptions. We are a Great Place to Work and welcome those who are intellectually curious and keen to see CFM’s thinking, research and analysis come to life in a way that benefits our clients.

Are you passionate about Research?
The success of CFM is borne from our scientific and collaborative approach to research; we value and invest significantly in R&D. If you’re a team-player, curious and want to contribute to pioneering research into financial markets, come and join our team!

Position :
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 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 statistical tools, exploiting recent theoretical models, 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.
The position will be held in Paris or New-York.

Ideal Candidate :

• PhD in experimental or theoretical science (life science, mathematics, physics, statistics etc.) or in a computational scientific field (big data, computer science, computational biology or chemistry, engineering,
• Post PhD experience (academic or private sector research),
• Taste for analysis of complex data sets, modelling and practical implementations in simulation environments,
• Programming skills in Python, C++,
• Adaptable and rigorous, capable of working in a quickly evolving environment,
• Strong teamwork and communication skills.

• HR Call
• Technical test
• Seminar
• Interviews