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Data scientist

Permanent contract
Paris
Salary: Not specified
Starting date: January 02, 2022
No remote work
Experience: > 3 years
Education: Master's Degree

Capital Fund Management
Capital Fund Management

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Questions and answers about the job

The position

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.

The context

As pioneers in scientific, quantitative trading, we explore more and more datasets in order to shape and consolidate our trading decisions. The IT Data Analytics team works closely with Research to make predictive, statistical analyses, drawing on new exploratory data.

The job

As an expert on alternative data (text, geo-tracking, graph/network…) and time series, you will take part, from the exploratory phase up to production launches, in:
• Analysing new datasets for alpha research (structured and unstructured data)
• Extracting relevant features from these datasets to assist the Research teams
• Contacts with our data providers
• Understanding business issues in order to identify new modelling pathways
• Contributing to the development and maintenance of a test analytics platform
• Designing data prediction models
• Launching and monitoring analytics on alternative data


Preferred experience

Your profile :

• Engineering school or university equivalent (preferably a Master’s in Machine Learning or Data Science)
• Knowledge of programming and visualisation in Python
• Knowledge of data science tools and libraries (Numpy, Pandas, Matplotlib, Jupyter)
• Familiarity with several Machine Learning techniques and their libraries (Scikit Learn, Xgboost +Tensorflow and/or Pytorch and/or Keras)
• Knowledge in Natural Language Processing is a plus (NTLK, Spacy, Hugging Face)
• Familiarity with distributed computing tools and cloud technology is a plus (Spark, AWS)
• Versatile, autonomous and rigorous, with a strong team spirit and good communication skills
• Professional-level knowledge of English.

Your “plusses”:

• Inquisitive
• Good aptitude for synthesizing information
• Keen to develop in an environment that handles large volumes of data
• Production and result oriented
• Interested in financial markets

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