Researcher- Quantitative Finance (New York)

7 days left

Location
New York City, New York (US)
Salary
Unspecified
Posted
03 Dec 2021
Closes
01 Feb 2022

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 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 experience in the quantitative finance is required.

The position will be held in New York.

Ideal Candidate:

PhD in theoretical, experimental or computational science fields such as physics, mathematics, computer science or engineering.

Two years of professional experience or post doctoral experience is preferred.

Taste for analysis of complex data sets, modelling and practical implementations in simulation environments.

Proficiency in scientific programming. As part of the interview process, candidates will be required to code in Python.

Adaptable and rigorous, capable of working in a quickly evolving environment.

Strong teamwork and communication skills.