Capital Fund Management

Capital Fund Management


  • Prácticas 
  • Paris
  • Licenciatura / Máster
  • < 6 meses

La oferta


  • Prácticas 
  • Paris
  • Licenciatura / Máster
  • < 6 meses

¡El puesto ya ha sido cubierto!


Founded in 1991, Capital Fund Management (CFM) is a global quantitative and systematic asset manager applying a scientific approach to finance, combined with the latest technology to protect and grow our clients’ assets. Simply put, CFM analyses huge quantities of data, identifies patterns, develops trading algorithms and implements them efficiently on the global markets with the latest technology platforms.

As these techniques increasingly become the norm in asset management, CFM is looking for great minds to help the firm remain at the forefront of this sector.

Job description

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 Technology?
At CFM, we inspire innovation through a collaborative approach to work. Our Technology department represents 50% of our workforce and implements solutions to meet business teams’ expectations, whilst working with all CFM teams including Research and Investor Relations. If you are passionate about advancing technology, come and join our team!

The context
In recent years, asset management and investment banking have been focusing their attention on “alternative data”. This data describes the “real” economic world and not the financial one: geolocation of people using their mobile phone (employees or clients), credit cards usage, satellite images, texts, weather, occupation rate of hotels, job postings, etc.

To support efforts in this field, the role of Data Scout has emerged, which consists in exploring this new “ecosystem of information”, with the goal of maintaining a good picture of the current data landscape, of suggesting ideas to the teams that create investment signals, and of identifying appropriate data providers for a given research project.

CFM’s researchers and data scientists thus constantly test new data sets: they make sure that the data looks solid and is as expected, and then typically test trading ideas by simulating the trades from the strategy on historical data. If a data set looks promising, we then buy it and put new trading strategies in production. Computers will then perform trades automatically in a way that incorporates the new strategy.

The job

Join the Data Sourcing team and learn about a vast number of key and alternative data sets for finance. Get hands-on practice by interacting with dataset providers (the in-depth information that you will get is typically only provided to financial institutions like CFM). Interact with researchers and data scientists on what new data sets they could use.
• Be on the look for data sets that could be used in trading strategies (either on themes that are already identified, like oil, or on new themes that seem promising to you), and push for some of them.
• Interact directly with data providers and stay on top of the current status with each of them (first contact, ongoing tests, etc.)
• Make sure that the information gathered on data sets is well organized (in the CFM database and wiki, or in meeting agendas).
• Organize weekly or bi-weekly discussions with trading research teams on the latest news on relevant data sets you found, so as to decide which data sets should be tested.

Preferred experience

Your profile:
• A taste for producing well-organized information, presented in a clean and clear way (as we need the information on data sets to be easily usable in the future).
• Very good personal organization skills (as there are many providers to interact with at a given time).
• Very good international English level (written and oral, for communicating with data providers).
• Some finance background.

Appreciated skills:

• More than a basic background in finance.
• Python and Pandas knowledge.

Meet the team

This content is blocked
Youtube cookies are required to show you this content
Questions and answers about the offer
  • Añadir a favoritos
  • Compartir en Twitter
  • Compartir en Facebook
  • Compartir en LinkedIn