Researcher - Quantitative Finance (Paris) - Capital Management Fund

Capital Management Fund

Entreprise vérifiée

Paris, France

il y a 2 semaines

Posté par:

Sophie Dupont

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Description

Is CFM what you're looking for?
We're a pioneer in the field of quantitative trading, founded in 1991. We are innovative, collaborative and passionate about what we do.

What can CFM offer you?
We create a unique international environment for highly-talented and motivated people to explore new ideas and challenge assumptions.

We welcome talent that is intellectually curious and keen to see CFM's thinking, research and analysis to add value for our clients.

Are you passionate about Research?

The success of CFM is born 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 extracting insights from a vast array of datasets (e.g. traditional financial data, but also exotic alternative datasets) to develop sophisticated trading models. The aim is to build new strategies, to supplement those already devised and implemented by CFM.

You will be working in a team of more than 60 researchers in close collaboration with data and software engineers.

The work will consist in:

Scouting datasets;
Formulating new investment hypotheses;
Helping to onboard new datasets that can validate (or invalidate) these ideas;
Rigorously carrying out statistical tests (including backtests)
Implementing the additive robust trading insights into production.

The position will be held in Paris.

PhD in experimental or theoretical science (life science, mathematics, physics, statistics, economics, etc.) or in a computational scientific field (big data, computer science, computational biology or chemistry, engineering)
Post PhD experience (academic or private sector research),
Understanding of the ins and outs of machine learning algorithms—and can tweak them as needed
Experience with applied machine learning / econometrics to large datasets
Programming skills in Python
Adaptable and rigorous, capable of working in a quickly evolving environment,
Strong teamwork and communication skills.