Freelancer profile translated to English.

Description

ENSTA Paris 2022 Data Science Engineer, I have been supporting companies on their Data & AI projects for 4 years, from scoping to production.

My cross-functional background has allowed me to work in both industrial contexts with sensitive data (R&D at Thales DMS) and in consulting for large accounts (Forvis Mazars, Saegus), where I have designed AI agents (via MCP) for data enrichment and due diligence, as well as generative AI demonstrators for CAC 40 clients. On the technical side, I master the entire data chain: ingestion and pipelines (Python, SQL, Snowflake, Azure), modeling and machine learning (XGBoost, LightGBM, rigorous statistical evaluation), up to delivery via interactive dashboards (Streamlit, Power BI) or deployed applications (Docker, FastAPI, React).

Rigorous and autonomous, I enjoy immersing myself in my clients' business context to deliver robust and directly usable solutions, whether for a POC to be quickly scoped or a longer development mission.

Industry field of expertise

Languages

French
Native or bilingual
English
Fluent
Spanish
Conversational

Workplace preferences

Can work on-site

Paris (up to 20km)

Mazars
Data Consultant
CONSULTING AND AUDITS
November 2023 - September 2025 (1 year and 10 months)
Paris, France
Data Consultant at Forvis Mazars in La Défense, I developed Python/Alteryx pipelines on large-scale financial data for internal control optimization missions, producing analytical deliverables for international group executives.

Particular attention was paid to documentary rigor and GDPR compliance for all deliverables.
Data analysis Problem solving Python programming Microsoft Excel Alteryx
UNILEVER
Data Scientist
RETAIL (SMALL BUSINESS)
January 2023 - January 2024 (1 year)
Paris, France
Data Scientist at Unilever in Rueil-Malmaison, I supported sales teams in managing their performance in the French market by designing real-time Power BI dashboards, allowing precise and responsive monitoring of commercial KPIs.

This work involved structuring sometimes heterogeneous data sources, defining relevant indicators with business teams, and formatting clear and actionable visualizations for non-technical users.

In parallel to this work, I automated several structured data pipelines, reducing manual preparation work and ensuring the reliability of reporting updates.

This mission was also an opportunity to get started with DataBricks, laying the foundation for my appetite for large-scale data engineering, which I continued to develop in my subsequent missions.
Microsoft Power BI Databricks Data science Machine learning Marketing
Thales
R&D - Data & AI
DEFENSE AND MILITARY
September 2020 - August 2022 (1 year and 11 months)
78990 Élancourt, France
Apprentice Data Scientist at Thales in Élancourt, I applied machine learning methods to radar signal processing (CNN, DBSCAN, XGBoost) on real signals, developing and validating models on sensitive and large-volume data in a defense-classified environment.
Machine learning Data science Scikit-learn Streamlit Git

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Engineering degree, Mathematics and Computer Science
ENSTA Paris
2022
Diplôme d'ingénieur, Mathématiques et informatique
University Technology Diploma, Physical Sciences
Université Paris-Sud
2019
Diplome Universitaire Technologique, Sciences physiques