Jeanne Chaverot
À propos du candidat
Vous avez besoin de nettoyer et comprendre vos données? Vous aimeriez utiliser l’AI pour transformer ces données en un produit concrêt qui apporte de la valeur à votre business?
Entrons en contact!
Je suis data scientist, développeuse en machine learning depuis plus de quatre ans, passionnée d’informatique et de nouveaux projets.
✅ Nettoyage, Analyse & Visualisation de Données (Regex, Pandas, Seaborn, Matplotlib)
✅ Développement de Modèles prédictifs concrêts et utilisables (sklearn, TensorFlow, Pytorch)
✅ Optimisation de modèles de Machine Learning
✅ Mise en place d’une interface pour visualiser vos résultats (Docker, Streamlit, FastAPI)
🎓 Formation: Ecole Polytechnique Fédérale de Lausanne, #14 QS World University Rankings 2022
👩🏼💻 Experience: NLP, Time Series, Analytics, Segmentation, Image Analysis, Deep Learning, Convolutional Neural Networks, Data Science Workshops
Location
Education
Data Analytics Machine Learning / Artificial Intelligence Deep Learning / Convolutional Neural Networks Graph Theory Natural Language Processing
Travail & Expérience
Integrated the IBM Consulting team as a data science engineer I worked closely with IBM clients to understand their needs and suggested implementable solutions, designed successful proof-of-concept solutions to answer clients’ needs, and updated IBM data visualization platform to keep track of the Sales team statistics
Lead Data Scientist of the company. Designed the data centre nomenclature, successfully allowing any algorithm to access the required objects from the data centre Implemented a sales analytics pipeline to create visualizations allowing the business development team to use concrete results during client and investor meetings Developed a segmentation algorithm for time-series cellular imaging data resulting in a complete automation of cell-development tracking Worked on a deep learning network for product defect detection and classification to avoid sending faulty products to clients
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