Intern (m/f/d) in the range of Global Market Data and Artificial intelligence Lab, Frankfurt am Main

DAB BNP Paribas ist die Bank für unabhängige Vermögensverwalter, Fondsvermittler, Anlageberater und institutionelle Kunden. In Deutschland führen bereits mehr als 60% aller bei der BaFin zugelassenen Finanzportfolioverwalter ihre Endkundendepots bei uns. Damit sind wir in diesem Segment der klare Marktführer! Für unsere Kunden sind wir heute ein stärkerer Partner denn je: Als Teil des großen Netzwerkes unserer Muttergesellschaft, der französischen BNP Paribas.

Responsibilities

• participate to the life of the LAB
• take ownership of a couple of projects within the ones that we will be identified at the time of joining
• typical topics
  
• product recommendation for our clients (within a given asset class, or cross-assets, on listed markets, primary market or secondary markets)
• natural language processing
• unsupervised classification of the various market participants behavior
• prediction of flows on our client franchise
• relative value between different assets
• sentiment analysis in chats or news
• extraction of relevant information in social media sources
• improvement of the market making in low or high frequency

Profile

• love working with data but are not afraid to deal with the hard problems associated to it: a big part of our job is indeed about gathering the data, understanding it, cleaning it, normalizing it and finally extracting what will be relevant to the problem in a usable format
• are delivery driven, who know what it takes to build a robust application, who like to code but will pay attention to details as their work will go quickly in production and will be used on a daily basis by the thousands of employees of BNPP who expect high level of reliability
• love to spend time modelling, being innovative in their solution, who don’t mind pressure and are not afraid to fail, and who understand that to go big, we first need to start small
• have coding skills and have been exposed to machine learning (ex: TensorFlow, Keras, Sklearn) is a must