Crédit Agricole CIB - 12 Month Internship - FX Quantitative Intern
Crédit Agricole CIB
Publiée le
31/07/2026
Contrat
Stage · 7-12 mois
Localisation
London
Taille équipe
Inconnue emp.
Rémunération
Inconnue
Missions clés
Assister le team in gathering information and data for FX forecasting report preparation · Préparer des templates for research documents ahead of publication · Update PowerPoint and Power Bi presentations · Ensuring data accuracy for charts and consistency in forecasts across publications · Mettre le profit/loss record of trade recommendations · Support the update · Maintenance · Développer vos compétences et accéder diverses mobilité opportunità among les diversités de notre entreprises dans plus que 30 international locations.
Profil recherché
0-1 ans d'expérience · Rigueur · Esprit d'analyse
Outils & compétences
SQL, Python
Le poste en détail
Join our team as an FX Quantitative Research Intern. This role is perfect for individuals passionate about economics, finance, capital markets and derivatives. You will support the FX research team in maintaining databases, fulfilling client data requests and assisting in the preparation of research documents/presentations. The ideal candidate will have a strong background in economics or a related field and experience with quantitative tools and data analysis. Key Responsibilities are, but are not limited to: Assist the team in gathering information and data for FX forecasting or report preparationPrepare templates for research documents ahead of publicationUpdate PowerPoint and Power Bi presentations, ensuring data accuracy for charts and consistency in forecasts across publicationsMaintain the profit/loss record of trade recommendations, pricing trade ideas in spot, vanilla, and exotic options, as well as interest rate futuresSupport the update, maintenance, and development of quantitative tools and databasesAssist in integrating existing research quantitative tools into the global research platformExplore opportunities for developing new quantitative tools and identify projects to enhance the team’s forecasting ability