Stagiaire Modélisation Risque de Crédit et Qualité des Données (H/F) – Modélisation Quantitative, Qualité des Données

Job Description

Analyste Quantitatif Risque de crédit IRB Retail | Societe Generale

The Tone:
This is a 6-month internship at Societe Generale, likely located in France with hybrid work options. The RISQ/MDL/MOD team within the Risk Directorate is responsible for developing, recalibrating, monitoring, and maintaining regulatory credit risk models used for IRB and IFRS 9, as well as climate stress testing and operational risk. This role is crucial for strengthening the quality of data used in quantitative modeling and actively contributing to the development and oversight of these essential regulatory credit risk models, ensuring robustness and regulatory compliance.

The TL;DR
• Role: Internship
• Type: Temporary
• Location: Hybrid – France

• Team: RISQ/MDL/MOD within Societe Generale’s Risk Directorate
• Mission: Contribute to enhancing data quality for quantitative modeling and participate in the development and monitoring of regulatory credit risk models.
• Tech Stack: Python, Power BI, Tableau, Excel, databases

What You’ll Actually Do
• Develop Python tools, indicators, and dashboards to establish a framework for monitoring modeling data quality.
• Automate data controls, identify anomalies, and track quality indicators to improve data reliability and operational efficiency.
• Harmonize data practices and disseminate best practices across various modeling teams.
• Conduct quantitative analyses, participate in model performance studies, and support model recalibration projects.
• Contribute to the development, recalibration, and ongoing monitoring of regulatory credit risk models.

The Must-Haves
• Background: Master’s Degree (last year of engineering/business school with a quantitative finance specialization, or university Master 2) in statistics, data science, applied mathematics, IT decision-making, or risk management. Entry-Level.
• Experience: 6-month internship. Solid knowledge in statistics, data analysis, and programming; proficiency in Python for data manipulation, analysis, and visualization.
• Skills: Python, Excel, database exploitation, analytical rigor, critical thinking, strong organizational skills.
• Bonus: Knowledge of Power BI, Tableau, or equivalent reporting/data visualization tools; ability to be proactive and propose innovative ideas; autonomy; proficiency in written and spoken English.