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Salary
≈ $44k – $75k per year (Estimated)
Location
Hybrid (Montrouge, France)
Employment
Internship

Confirmed on the employer's own hiring board on Oct 19, 2026. First seen by Alion on Oct 3, 2026.

Overview
Company
Impact
Profile match
Crédit Agricole is a French cooperative banking group headquartered in Montrouge near Paris, covering retail banking through its regional banks and LCL, corporate and investment banking, insurance, consumer finance and asset management. It is described as the largest cooperative financial institution in the world, and its subsidiaries include Amundi, one of the ten largest asset managers globally, Crédit Agricole CIB, UBAF and the Crédit Agricole Group Infrastructure Platform. The group careers site advertises internships and permanent roles for business account managers, economists, energy and finance analysts, ESG project officers, compliance analysts and mainframe database engineers.

Rejoignez Crédit Agricole S.A., une institution bancaire de premier plan. En tant que stagiaire Data Scientist, vous contribuerez à l'enrichissement des analyses de marché et de la connaissance client, ainsi qu'à l'évolution de nos outils. Vous serez en charge de la conception et du développement de restitutions dans un environnement PowerBi, ainsi que d'une étude statistique sur le marché des entrepreneurs. Vous participerez également à l'amélioration continue des rapports existants et des processus de restitution.

Missions

  • Conception et développement de restitutions dans un environnement PowerBi sur le marché des particuliers et les marchés spécialisés.
  • Réalisation d'une étude statistique sur le marché des entrepreneurs, impliquant l'analyse de données et la modélisation de la population cible.
  • Participation à l'amélioration continue des rapports existants et des processus de restitution réalisés au sein du service.

Profil recherché

Data, Finance

Compétences techniques :

  • Expériences de l’outil PowerBi
  • Connaissances du langage SQL
  • Connaissances en Python
  • Connaissances en modélisation statistique / machine learning

Compétences générales :

  • Curiosité et force de proposition technique
  • Rigueur analytique
  • Esprit d’équipe et capacité de travail en équipe
  • Intérêt pour le secteur bancaire
  • Capacité d’écoute, d’analyse et de vulgarisation des processus techniques

Outils informatiques :

  • PowerBI
  • Python
  • SAS Viya
  • Suite Microsoft Office
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