À propos de Pauline
- Machine Learning: recommendation systems, ranking, personalization, deep learning, scoring, (PyTorch, TensorFlow, Scikit-learn), LLMs / GenAI
- Analytics Engineering: SQL-first data modeling, analytics pipelines, data quality & metrics
- Production & MLOps: CI/CD, monitoring, scalability, low-latency systems
- Senior Data Scientist (product, ML, recommender systems)
- Analytics Engineer (data modeling, decision support)
Français
Bilingue ou natif
Anglais
Capacité professionnelle complète
Expériences
- leboncoinEngineering ManagerE-COMMERCEseptembre 2023 - décembre 2025 (2 ans et 3 mois)Paris, France
Machine Learning & Recommender Systems – Homepage
- Mentored and supported a cross-functional team of 9 people (Data Scientists, ML Engineers, Backend/Frontend Developers, QA, contigent workers), contributing to stronger engagement and overall team performance
- Co-designed and launched a ML-powered personalized homepage (ad recommendations and dynamic ranking) with the Product Owner, resulting in a 10% increase in leads
- Led multiple large-scale technical initiatives, including: deployment of a vector database (Milvus) for real-time similar ad recommendations, infrastructure migration of the visual search feature covering 80M items, under strict production constraints, scaling of the recommendation system from leboncoin to Kleinanzeigen, expanding reach by 35M users, and delivery of a new homepage vision, enabling users to resume activity and discover relevant content
- leboncoinSenior Data ScientistE-COMMERCEdécembre 2019 - août 2023 (3 ans et 8 mois)Paris, France
Machine Learning & Recommender Systems – Homepage
- Developed and deployed a homepage recommendation system, serving 15M+ monthly users, using deep learning models for item suggestions across text, image, and tabular data
- Built deep learning models for seller recommendations, using collaborative filtering
- Implemented MLOps practices with Kubeflow pipelines for automated training and inference
- Stack: Python, TensorFlow, Kubeflow, Milvus, Kubernetes, Docker, Poetry, Spark, AWS
- DeezerData ScientistE-COMMERCEseptembre 2017 - novembre 2019 (2 ans et 2 mois)Paris, France
Machine Learning – BI & Data Science Team
Developed machine learning modelsfor churn prediction, user clustering, and survival analysisOptimized BI processes and automated KPI calculationsWorked closely with Product, Marketing, and Business teams to translate business needs into actionable data-driven solutions and support strategic decision-making.Stack: Python, Scikit-learn, Spark (Scala)
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Formations
- MasterÉcole Polytechnique2017Master in Data Science and Machine Learning • Key coursework: Machine Learning, Statistical Learning Theory, Optimization for Data Science, Kernel Methods, Database Management, Deep Learning, Machine Learning for Text and Graph • Developed strong programming skills in Python
- MSc inEngineering–MajorÉcole Nationale des Ponts et Chaussées2017Major in Industrial Engineering and Operations Research • Key coursework: Applied Mathematics, Statistics and Data Analysis, Corporate Finance, Design Thinking, Marketing, Supply Chain Management