Résumé
Third-year student at ENSAI, specializing in statistics and quantitative methods, with two internship experiences in financial markets. My background combines mathematics, statistics, econometrics, and programming, with hands-on experience in financial modeling, market risk, and Python.
With a strong interest in quantitative finance and data-driven approaches to financial markets, I am currently looking for a final-year internship in quantitative finance.
Expériences professionnelles
Quantitative analyst intern - market/counterparty risk
Societe Generale Corporate and Investment Banking - SGCIB , Puteaux - Stage
De Mars 2026 à Septembre 2026
Cross Asset Derivatives Portfolio - (over €200bn in client assets serviced).
• Greeks and Stress-Testing Analysis for daily Monte Carlo VaR Model Certification and P&L Backtesting
• Python automation project for VaR sanity checks and P&L backtesting reports
• Presentation of the daily P&L backtesting and the VaR sanity check reports to the MARK Front Office team.
• Collaboration with the Bangalore team (India).
Alm quant
La Banque Postale , Paris - Stage
De Septembre 2025 à Février 2026
• Recalibrated behavioral balance sheet models and developed econometric forecasting engines using Vector Error Correction Models (VECM) to challenge banking margins.
• Assessed model risk and stress-test impacts on key Asset Liability Management (ALM) metrics.
• Engineered and deployed a rigorous shared Python library for the quantitative analytics team, standardizing core pricing and statistical routines.
Research intern in machine learning
VegaSpark Technologies , Paris - Stage
De Juin 2025 à Août 2025
• Processed and structured large-scale datasets (millions of records) using Python (Pandas, NumPy), handling missing data and anomalies.
• Engineered features and applied data transformations (scaling, encoding, dimensionality reduction) to enhance model performance.
• Built and evaluated supervised learning models (logistic regression, decision trees, random forests) with scikit-learn.
• Applied cross-validation techniques and performance metrics (ROC-AUC, precision, recall) to ensure robustness and reliability.
• Gained end-to-end experience in machine learning pipelines in a production-oriented environment.
Quant intern
Trade Value
De Juin 2024 à Juillet 2024
Study and computer modelling of a finance article about pricing call option presenting an innovative method for calculating implied volatility using the Black-Scholes formula for an European share, thus providing a more accurate and rapid solution for market finance professionals.
Visit Socitété Générale's trading rooms and meet the people who work there.
Supervised by Abdelmalek El Alaoui (see his recommendation on my profile).
Mathematics tutor
De Octobre 2023 à Juin 2025
Support several students from middle school to final year (Terminale) in mathematics, helping them build a solid understanding and achieve their academic goals.
Formation complémentaire
Stage de rechercher en Machine Learning
Vega Spark Technologies - Machine Learning, Data, Python
2025 à 2025
• Cleaned and preprocessed large datasets (millions of records) using Python (Pandas, NumPy), handling
missing data and outliers.
• Engineered features and applied transformations (normalization, encoding, dimensionality reduction)
to improve models.
• Built and evaluated supervised ML models (logistic regression, trees, random forests) with scikit-learn.
• Used cross-validation and metrics (ROC-AUC, precision-recall) to ensure model robustness.
• Managed end-to-end ML pipelines from data processing to interpretation in a production setting.
Parcours officiels
Langues
Français - Langue maternelle
Anglais - Courant
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