Contrôleur Financier
BNP Paribas
de, France, PARIS
il y a 2j

BNP Paribas Asset Management is the investment management arm of BNP Paribas , one of the world’s major financial institutions.

Managing and advising EUR 580 billion in assets as at 31 March 2017, BNP Paribas Asset Management offers a comprehensive range of active, passive and quantitative investment solutions covering a broad spectrum of asset classes and regions.

The Quant Research Group was created 10 years ago with the objective of centralizing all quantitative resources in one team and developing a strong quantitative culture at BNP Paribas Asset Management .

The Quant Research Group is now well established in BNP Paribas Asset Management and remains at the core of its strategy.

The executive committee of BNP Paribas Asset Management is now supporting the expansion of the Quant Research Group to increase further the impact of quantitative research in the activity of the company.

The Quant Research Group transversal position and quantitative expertise acquired since its creation will be instrumental in this respect.

The Quant Research Group is looking to hire, in Paris , a data scientists / quantitative analysts to strengthen its research capabilities and in particular to meet BNP Paribas Asset Management’s ambition to leverage big data as source of information for generating investment performance.

  • Your missions are : - Providing support to your team and participating in the investment’s review processes by sharing your best practices;
  • Participating in our "smart beta" development by playing a key role in the research and development of BNP Paribas Asset Management's factor investment strategies in equities and fixed income;
  • Contributing to the design of customized and innovative solutions for your clients;- Participating in the writing of articles in journals (specialized or not);
  • Testing different databases and applying the most relevant techniques for each database. Qualifications :
  • Advanced degree in quantitative disciplines;
  • 10 years experiences working with large data sets ;
  • Solid numerical programming abilities ;
  • While we analyze the data-rich domain of finance.
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