Freelancer profile translated to English.

Description

Financial Data Scientist graduated from ENSAI, with over 8 years of experience in leading financial institutions (Deloitte, BPCE, CDC). I bring a unique triple expertise:

Programming & data engineering: Python, R, C++, SQL, MLOps

Data science & predictive modeling: ML, time series, Monte Carlo simulation, copulas

Banking risk & regulation: IFRS 9, IRB/Basel II–III–IV, ALM (EVE, liquidity), solvency, climate and prudential stress tests

I work on the entire model lifecycle, from data structuring and methodological development to independent validation, industrialization, and production of regulatory indicators (PD/LGD/EAD, IFRS 9 provisions, VaR/ES, economic capital, ΔEVE, MVM).

My goal: strengthen your models, secure your regulatory compliance, and accelerate your risk transformation projects through a rigorous, tool-driven, and results-oriented analytical approach.

Languages

French
Native or bilingual
English
Fluent

Workplace preferences

Can work on-site

Paris (up to 50km)

Groupe Caisse des Dépôts
Financial Data Scientist
BANKING AND INSURANCE
May 2022 - Today (4 years and 1 month)
Paris, France
Specialist in Solvency Risk and Economic Capital, including the integration of emerging risks (Climate).
My main tasks are:
• Solvency & Capital: Production of Solvency indicators, calculation of Economic Capital, estimation of Unexpected Losses (VaR, Stress Tests), and Backtesting (Monte Carlo).
• Risk Analysis: Calculation of marginal contributions (Shapley) for capital allocation. Modeling of risk on real estate assets.
• Climate Risk Pioneer: Implementation of Climate Stress Tests (NGFS) and evaluation of climate capital requirements (VaR).

Technical Mastery:
• Methods: Monte Carlo Simulation (NSSF), Copula, VaR/ES, Kupiec Tests, Multi-objective Optimization.
• Tools: ALM Software (Risk Pro), R, Python, VBA, Alteryx, MySQL.
Gestion Actifs et Passifs Risque de taux Stress-test Python VaR MonteCarlo
BPCE SA
ALM Manager
BANKING AND INSURANCE
March 2019 - April 2022 (3 years and 1 month)
Paris, France
Expert in Financial Modeling and Asset-Liability Management (ALM), specializing in the validation of Housing Savings models and the quantification of prudential risks (EVE, CET1).
My main missions are:
• Core Competencies: Model validation, backtesting, ALM/prudential impact analysis, formulation of compliance recommendations.
• Advanced Techniques: Construction of complex predictive models (ARIMAX time series, Neural Networks LSTM) to anticipate customer behavior.
• Industrialization: Automation of reporting and forecasting via Python (TensorFlow), R/Shiny, and Power BI.

Technical Mastery:
• Languages & Libs: Python (TensorFlow), R, SAS.
• Methods: ARIMAX, LSTM, Genetic Algorithm, X12 Arima.
• ALM/BI Tools: FERMAT (Moody's), Shiny, Power BI, Kibana.
Python Machine learning Gestion Actifs et Passifs Risque de taux Risque de liquidité
Deloitte
Quantitative Analyst
BANKING AND INSURANCE
November 2016 - January 2019 (2 years and 2 months)
Paris, France
Expertise in IFRS 9, Credit Risk, and Machine Learning (Basel / IRB):
• IFRS 9 Modeling & Compliance: Implementation and validation of IFRS 9 parameters (PD, LGD, CCF, EAD). Counter-calculation of provisions and production of FinRep reporting. Definition of Homogeneous Risk Classes (HRC).
• PD Performance (IRB): Improvement of PD models using Machine Learning (Random Forest, Neural Networks) and portfolio segmentation by clustering (DBSCAN).
• Data & Governance: Management and quality control of large volumes of data (JSON). Formulation of recommendations for model robustness and governance.

Technical Methods and Tools:
• Methods: Random Forests, Boosting, Neural Networks, Logistic Regression, DBSCAN.
• Tools: R, h2o, SAS (Guide/VA/ECL), fLite (Shiny), Java.
Machine learning Modélisation Gestion du risque de crédit IFRS9 Bâle III