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. We are innovative, collaborative and believe in diversity with around 30 nationalities, across our offices around the world.

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!

The context
ESG principles are becoming a pivotal dimension in the investment industry.
CFM is at the forefront of this exploration as witnessed by the recent launch of an investment program which has the ambition – among others - to encompass the E pillar with strategies aware of the energy transition and climate changes.
The challenge to incorporate those principles into viable strategies is twofold: i) on one hand we need to select and build metrics which are relevant for the dimension want to include, e.g. how to measure the exposure of a firm to a carbon tax, how to measure the exposure of the assets of a firm to extreme weather events, etc. ii) and on the other hand, we need to assess when these metrics are becoming financial material. This latter point is very specific to the fact we want to include dimensions which are related to a transition. In an equilibrium regime, the former aspect is typically more important than the latter. The energy transition is instead the rollout of a paradigm change towards sustainable economic systems and, in this perspective, it is intrinsically an out of the equilibrium phase. In such a regime, both the assessment of the drivers and their materiality deserves the same level of importance.

The job
The internship is aimed at investigating the latter axis, the assessment of the materiality of the E pillar (not necessarily only E, but we will devote a special focus on E).
The intern will deal with different sources of data to assess the materiality, mainly ESG-specific NLP datasets, and possibly other sources to assess the materiality e.g. trends of investment fluxes, etc.

Your profile

• Fluency in Python (numpy, scipy, pandas, scikitlearn, etc)
• Statistical methods for data analysis

Desirable but not mandatory

• previous experience of dealing with large datasets (statistical analysis)
• experience of ML techniques.
• ESG (any knowledge)