Freelancer profile translated to English.
Back to original languageAbout Thibaut
💡 Available for freelance from mid-July to mid-November 2025 for Data Engineering / Data Science missions, fully remote or on-site (Paris, Lyon, Dijon).
During this period, I can dedicate myself full-time to your data projects:
Data ingestion and transformation (ETL in Python / SQL)
Analysis, modeling, and preparation for production
Pipeline automation and reporting
Deployment of APIs or analysis tools
📆 From mid-November to mid-April, I remain available for fixed-price projects or ad-hoc interventions:
Python/SQL pipeline creation
Automation scripts and data cleaning
Analytical dashboards and reporting
Model industrialization and deployment via FastAPI
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🎯 My approach:
Quick understanding of your business challenges
Integration into your existing environments
Design of simple, robust, and efficient solutions
Progressive, documented delivery, aligned with your priorities
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🔧 Technical Stack
Languages: Python, SQL
Libraries: Pandas, NumPy, Scikit-learn, Plotly, Seaborn
ETL & Transformation: Python, SQL, dbt
Storage: Snowflake, PostgreSQL, SQLite
APIs & Apps: FastAPI, Streamlit
Automation: Python Scripts, Lightweight CI/CD, Airflow
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💬 Profile: Pragmatic Data Engineer / Data Scientist, autonomous, attentive, with an approach focused on added value and concrete results.
My goal: to help you get the most out of your data by building clear, reliable, and high-performing pipelines.
French
Native or bilingual
English
Conversational
Spanish
Conversational
Can work on-site
Dijon (up to 50km), Paris (up to 50km), Lyon (up to 50km)
Experience
- Maternité-Projet FinalData ScientistJanuary 2025 - April 2025 (3 months)Dijon, FranceCleaning and exploration of the medical dataset provided by a statistician from a regional maternity hospital.Medical feature engineering from clinical variables (age, history, labor duration, etc.). Supervised modeling: comparison of models (Logistic Regression, Random Forest, XGBoost).Evaluation & interpretability: confusion matrix, ROC curves, SHAP values.Experiment tracking with MLflow.Deployment of a Streamlit app for interactive model demonstration to non-technical users (e.g., midwives, doctors).
- Formation JedhaData Scientist - Training ProjectMarch 2025 - April 2025 (1 month)🚗 Optimizing delays & pricing API – Getaround🎓 Certification Project – Fullstack Data Scientist Training, Jedha🛠️ Technologies: Python, Pandas, Streamlit, Scikit-learn, FastAPI, Docker, Hugging Face Spaces, GitHub---🎯 Project Objective:Reduce vehicle return delays on the Getaround platform by proposing a strategic analysis for introducing a minimum interval between rentals, and deploying a predictive pricing API usable by vehicle owners.---🔍 Work Performed:🧠 Rental Delay AnalysisStudy of late returns based on check-in methods: Mobile, ConnectSimulation of different threshold scenarios (15, 30, 60 min) to quantify affected rentalsEstimation of potential revenue loss for ownersVisualization with Streamlit Dashboard (Hugging Face web sharing)🤖 Predictive Pricing ModelPreprocessing of the pricing_project.csv file (normalization, feature selection)Training a regression model (RandomForestRegressor)Performance evaluation on test set (RMSE, MAE)Building a /predict endpoint with FastAPI to predict an optimal price🌐 Full Online DeploymentDeployment of the application on Hugging Face Spaces (Streamlit + FastAPI)Creation of dynamic documentation /docsHosting code on GitHub with README and local execution instructionsTesting the API with curl and JSON POST requests---📈 Results:Interactive dashboard allowing the product team to test the impact of the threshold by car typePublicly accessible API capable of providing an optimal price for a given rental configurationDeployment of a complete solution combining Data Analysis, ML, and DevOps
- FreelanceFreelance Data ScientistApril 2024 - Today (2 years and 2 months)• Development of the VITIZEN mobile application for winegrowers (Android Kotlin + Python backend, Firebase)• Design and implementation of a RAG-type AI assistant for consulting agricultural technical documents• Proof of concept for predicting the risk of severe postpartum hemorrhage (classification model, evaluation)• Deployment of data microservices with FastAPI and Docker for rapid prototyping
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Education
- Data Science Developer DesignerJedha Bootcamp2025Formation Data Scientist Fullstack – Jedha (450h) Certification RNCP – Paris / en ligne – 2024–2025 Programme intensif couvrant l’ensemble du cycle de vie d’un projet data : Python & analyse de données (Pandas, Numpy, Plotly, scraping, APIs) Machine Learning & Deep Learning (classification, clustering, réseaux de neurones) Big Data & Cloud (PySpark, Databricks, stockage AWS) Déploiement de modèles (FastAPI, Docker, mise en production) Approche orientée projet avec mises en situation concrètes et préparation à des postes opérationnels : Data Scientist, ML Engineer, Data Engineer.