Freelancer profile translated to English.

Description

AI Engineer with a PhD in Artificial Intelligence and over 7 years of experience in designing intelligent data-driven solutions for the retail, marketing, and energy sectors. I specialize in transforming complex data into actionable insights for businesses through data analysis, machine learning, and large language models (LLMs). I offer end-to-end expertise, from data engineering and preparation to model development and deployment, with a strong focus on creating concrete and measurable impact.

Languages

French
Native or bilingual
English
Fluent

Workplace preferences

Can work on-site

Paris (up to 50km)

ENGIE
Senior AI Engineer
ENERGY AND UTILITIES
September 2025 - Today (11 months)
Paris, France
Development and deployment of agents, creation of tools for the agent, deployment of Vector Search for RAG, LLM evaluation as a judge, Tracing and monitoring with MLflow, production deployment on Databricks.
Langchain LangGraph MLflow Databricks Python
Kiliba
AI Engineer / Data Scientist
RETAIL (SMALL BUSINESS)
April 2021 - August 2025 (4 years and 4 months)
Ile-of-France, France
Comprehensive improvement of the email campaign sending chain, from data engineering to contact targeting, including product recommendation and email preparation.

- Design, optimization, and maintenance of large-scale data processing workflows on AWS and Databricks, using SQL, Python, and Spark.
- Migration of data processing pipelines from Scala Spark to PySpark, including refactoring, performance optimization, and code maintainability improvement.
- Design and deployment of advanced customer segmentation and targeting strategies, with improvement of the RFM method for increased accuracy.
- Development of personalized recommendation systems: collaborative filtering (ALS) and content-based recommendations (cosine similarity).
- Experimentation, tracking, and deployment of recommendation models with MLflow, integration of production pipelines on Databricks via Terraform.
- Implementation of automated unit tests with Pytest to ensure code quality, reliability, and robustness.
- Calculation of embeddings and use of RAG for the design of a chatbot that contextually recommends products.
- Use of LLMs for real-time product recommendation via AWS Lambda.
- Development of multi-agent workflows for scraping, web search, and event planning related to e-commerce stores, leveraging OpenAI, LangChain, and LangSmith APIs.
- Conducting advanced analyses of email marketing campaigns and creating interactive dashboards to track KPIs (click-through rates, conversion rates, ROI).
- Deployment of A/B testing strategies to optimize campaign performance, generating measurable gains in user engagement and revenue.
- Analysis and formalization of data science needs in close collaboration with business teams and the Product Owner.
Python Spark LLM Machine Learning Data Analysis
Atomic Energy and Alternative Energy Commission (CEA)
Data scientist
ENERGY AND UTILITIES
October 2017 - December 2020 (3 years and 2 months)
Lille, France
Development of an innovative approach to fault prediction for industrial systems.

- Design and development of a new approach to fault prediction for industrial systems.
- Application of advanced statistical and signal processing techniques to extract relevant indicators from industrial vibration data.
- Implementation of automatic indicator selection methods, significantly improving machine health monitoring and predictive maintenance performance.
- Early detection of degradation using anomaly detection techniques (OCSVM, AutoEncoder).
- Prediction of Remaining Useful Life (RUL) with limited historical data using Generalized Linear Models (GLM).
- Development of an innovative deep learning approach combining CNN and LSTM for RUL prediction from multiple historical datasets.
Valorization of results through presentations at international conferences (ECML, ICMLA, PHM Society).
Python Machine Learning Deep Learning Time Series Data Analysis