Global Markets (GM) is BNP Paribas’ capital markets business, delivering investment solutions across a wide range of asset classes and industry-leading services. As world leader in derivatives, BNP Paribas Global Markets offers clients tailored products, state-of-the-art trading, processing systems, research and strategic advising from its teams of experts, while also maintaining a sustainable economic model.

The Global Markets Quantitative Research division is in charge of the modelling, pricing & risk management developments for the entire offering of products within the Global Marketsactivity. The team operates globally with representatives in London, Paris, Asia and New York and plays a critical role in providing innovative solutions.

This requires a strong and permanent cooperation with trading and the Global Markets IT division to ensure all quant developments integrate optimally with the IT ecosystem, thereby ensuring the best deliveries to the business.

GM Labs is a spin-off quantitative research team which mandate is to build the next generation of Data Intelligence and language understanding products used in BNP Paribas GlobalMarkets. This small team works on projects using the latest techniques in Artificial Intelligence, Data modelling and Natural Language Understanding. The GM Lab collaborates closely with other Business, Quant Research and Technology teams.

The projects leverage the latest techniques on Machine Learning/Deep Learning.


  • Very strong background in mathematics, applied mathematics, statistics and computer science (at least MA/MSc level, Engineer school/ PhD from university a plus)
  • A post-graduate degree in Machine Learning, Artificial Intelligence or a related technical field is a strong plus (any ML background will be considered)
  • No finance background necessary


Typical experience required (equivalent practical experience accepted):

  • Experience in developing a concrete project using machine learning models, ideally experience to deliver cognitive/predictive systems to production
  • Experience in working in a Big Data environment, for both data manipulation and parallelisation of machine learning techniques (Hadoop/Spark)
  • Experience using Business Intelligence and statistical analysis software


Technical skills

  • Ability to drive technical development and prototyping in a fast-paced startup-like environment
  • Strong understanding and ability to apply advanced mathematical concepts to solve real world problems
  • Hands-on experience of Python, R, Scala
  • Strong background in Natural Language Processing
  • Knowledge of advanced visualisation, reporting tools (Tableau, Qlikview,d3,Spotfire,..)


Soft Skills

  • Good interpersonal skills.
  • Able to work autonomously within the requirements of the project and the quant team.
  • A flexible, hands-on attitude and willingness to make things happen.

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