Global Quantitative Research Analyst – Off-Cycle (Paris)

Bank of America

Paris

Hybride

EUR 16 000 - 22 000

Plein temps

Il y a 8 jours
Générateur de candidature

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Avantages offerts par ce poste

Competitive salary and benefits

Résumé du poste

Bank of America is seeking a Quantitative Research, Off-Cycle Intern in Paris to learn derivatives and contribute to the development of quantitatively-driven systematic strategies. You will engage with global quant teams, utilize diverse datasets, and support back-testing infrastructure within a fast-paced asset management environment.

The role emphasizes rigorous quantitative analysis, programming in Python/R/Matlab, and strong communication skills.

Qualifications

  • Pursuing a Bachelor’s or Master’s degree with completion between Sept 2027 and July 2028.
  • On track for minimum 2:1 degree classification (or equivalent).
  • Experience in developing and backtesting quantitative strategies in Equities or FICC.
  • Strong proficiency in time series analysis and big datasets.
  • Exposure to machine learning, NLP or information theory is a plus.
  • Excellent written/presentation skills and attention to detail.

Responsabilités

  • Learn about derivatives and quantitative strategies, contributing to research.
  • Work on back-testing infrastructure and diverse datasets under real-world constraints.
  • Present project findings to multiple research teams and stakeholders.
  • Coordinate with global quant research teams and cross-asset client solutions groups.

Connaissances

Quantitative research
Programming
Statistics
English fluency

Formation

Bachelor's/Master's in quantitative field

Outils

Python
R
Matlab
SQL
VBA
Excel

Description du poste

Bank of America is seeking a Quantitative Research, Off-Cycle Intern in Paris to learn derivatives and contribute to the development of quantitatively-driven systematic strategies. You will engage with global quant teams, utilize diverse datasets, and support back-testing infrastructure within a fast-paced asset management environment.

The role emphasizes rigorous quantitative analysis, programming in Python/R/Matlab, and strong communication skills.

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