Freelancer profile translated to English.
Back to original languageAbout Marguerite
Data scientist since 2022, with 10 years of professional experience, I help companies in the concrete exploitation of their data to generate measurable business impact.
My goal: to save you time and money through the exploitation of your data!
My main areas of intervention:
🧑💻 Data & Analytics:
- identification of data opportunities
- creation of analytical dashboards
- structuring and data validation
🤓 Machine Learning, for example:
- customer scoring (CLV)
- fraud detection
- churn prediction
- stock optimization
- recommendation systems, etc.
🤖 Automation & AI, for example:
- prompt engineering
- multilingual chatbots
- content creation / generation
- document processing
- process automation, etc.
I place particular importance on pragmatic solutions that are quick to deploy and adapted to the constraints of organizations without a data team.
Technical Stack:
- Python: Pandas, NumPy
- SQL: BigQuery, dbt
- n8n, Databricks
- GCP
- Data visualization: Tableau, Power BI, Metabase, Matplotlib
- ML & AI models: scikit-learn, Tensorflow, XGBoost, CNN, RNN, NLP, OCR.
- LLMs, RAG: Claude, OpenAI, Mistral, HuggingFace.
Available in hybrid mode in Lyon and Paris.
Available also remotely.
Contact me to discuss your challenges.
French
Native or bilingual
English
Native or bilingual
German
Conversational
Can work on-site
Lyon (up to 20km), Paris (up to 20km)
Experience
- Fairly Made®Data ScientistSOFTWARE PUBLISHINGJune 2024 - October 2025 (1 year and 4 months)Paris, FranceProjects:-Automatic document validation pipeline(CNN, OCR, LLMs, statistical methods) deployed in production -> 40% of documents validated without intervention (0 click, 0 min) and the rest validated in ~30s and 2 clicks, reducing average time per document by over 80% (vs 5 min manually).-AI Chatbot based on RAG and LLM pipelineto assist internal teams.- **Anomaly detection engine combining external API calls and statistical methods**. Designed and deployed machine learning & deep learning models for document analysis and anomaly detection (TensorFlow, Scikit-learn, GCP, Docker).Responsibilities:
- Exploratory Data Analysis (EDA) to identify trends, anomalies, and business opportunities
- Collection, cleaning, and transformation of structured and unstructured data
- Training and optimization of machine learning and deep learning models
- Development of solutions based on generative AI (LLMs, prompt engineering, fine-tuning, RAG)
- Model evaluation (cross-validation, metrics, hyperparameter tuning)
- Workflow orchestration with Airflow
- Data transformation with SQL and dbt in an analytical context
- Deployment and productionization of models with Docker, GCP, and API (FastAPI)
- Implementation of MLOps best practices (CI/CD, monitoring, model versioning)
- Creation of dashboards and visualization tools via Metabase and Power BI
- Communication of results to non-technical stakeholders
Stack: TensorFlow, Scikit-learn, Gen AI (LLM), dbt, Airflow, GCP, BigQuery, FastAPI, Docker, Metabase, Power BI. - Le WagonTeacher Data Science & Data AnalyticsEDUCATION AND E-LEARNINGOctober 2022 - January 2025 (2 years and 3 months)Paris, FranceSome projects:
- Satellite image segmentation to detect different types of agricultural crops: Yolov5
- Rap song lyric generation: RNN, Bert, LLMs.
- Detection of offensive messages: Naive Bayes classifier, RNN, CNN, Bert
- Emotion classification on images and videos: CNN
- Segmentation and classification of waste in images: Yolo and CNN.
Skills:- Data collection: API, Scraping, etc.- In-depth data analysis- Data Visualization- Machine Learning, Deep Learning & Gen AI: Knowledge of algorithms and model optimization- Model deployment and productionization- Data pipeline implementationTechnical Skills:- Python: Pandas, Numpy, Matplotlib/Seaborn, Scikit-Learn, Tensorflow, etc.- Computer Vision, Natural Language Processing (NLP), RNN, LLMs- MlFlow, Prefect- SQL: My SQL, PostgreSQL- dbt- Tableau, PowerBI - Le WagonTeacher Assistant in Data ScienceTECHApril 2022 - Today (4 years and 2 months)Bd Périphérique, Paris, FranceA bootcamp to learn about Data Science: Data analysis, Decision Science, Machine Learning, Deep Learning & Data Engineering.Python: Panda, Numpy, Matplotlib, Seaborn, scikit-learn, staatsmodel, Tensorflow, etc.SQL: DBeaver BigQueryMLFlow, Prefect, Google Cloud Platform (GCP)Tableau, Jupyter, Visual Code
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Education
- Data Science BootcampLe Wagon2022A bootcamp to learn about Data Science : Data analysis, Decision Science, Machine Learning, Deep Learning & Data Engineering. Python : Panda, Numpy, Matplotlib, Seaborn, scikit-learn, staatsmodel, Tensorflow, etc. SQL : DBeaver, Big Query MLFlow, Prefect, Google Cloud Platform (GCP) Tableau, Jupyter, Visual Code
- Master in Management (Grande Ecole program) specialization in MarketingNEOMA Business School2017Relevant courses : marketing research, operational marketing, data analysis, management accounting, financial analysis, negotiation technics, strategic marketing and innovation, brand management , distribution and trade marketing, marketing & design.