Quantitative researcher

il y a 1 jour

Paris, Île-de-France CAPITAL FUND MANAGEMENT Temps plein

Paris, 75, FR

ABOUT CFM

Founded in 1991, we are a global quantitative and systematic asset management firm applying a scientific approach to finance to develop alternative investment strategies that create value for our clients.

We value innovation, dedication, collaboration, and the ability to make an impact. Together, we create a stimulating environment for talented and passionate experts in research, technology, and business to explore new ideas and challenge existing assumptions.

ABOUT THE ROLE

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 100 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 candidate should be both creative, in order to imagine new ways of detecting hidden statistical patterns, and rigorous. Experience in manipulating datasets with machine-learning and/or econometrics is highly valued. Although a high interest in finance is crucial, no prior knowledge in the field is needed.

IDEAL CANDIDATE
  • 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
EQUAL OPPORTUNITIES STATEMENT

We are continuously striving to be an equal opportunity employer and we prohibit any discrimination based on sex, disability, origin, sexual orientation, gender identity, age, race, or religion. We believe that our diversity, breadth of experience, and multiple points of view are among the leading factors in our success.

CFM is a signatory of the Women Empowerment Principles.

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