À propos de Caroline
Senior Data Scientist (10+ years) ML & GenAI specialist. Built and deployed end-to-end ML solutions on AWS.
Strong in advanced Python, OpenAI/CrewAI/GoogleADK, time-series forecasting, BigQuery, SQL, and. experience working in cross-functional teams to deliver measurable business impact in operations and marketing.
Open to Lyon-based role (onsite 2-3 days/week).
Anglais
Capacité professionnelle complète
Français
Bilingue ou natif
Accepte de travailler sur site
Lyon (jusqu’à 10 km)
Expériences
- ConfidentielData scientistE-COMMERCEmars 2022 - mai 2025 (3 ans et 2 mois)Lyon, France
- Built production forecasting pipeline (Prophet + external regressors) achieving 15% MAPE. Automated training and deployment with CI/CD , integrated output into AdWords budget allocation workflows to improve campaign ROI. Tech: Python (pandas, NumPy), Docker, Git, CI/CD, BigQuery → (deployed to AWS SageMaker or equivalent),
- Designed geospatial analysis using H3 + Python to evaluate retail network coverage; developed a Streamlit decision-support app for field teams, enabling targeted expansion and reducing operating costs (estimated €500K). Tech: Python, H3, geopandas, Google Place API, Streamlit, BigQuery.
- Developed GenAI pipeline (LLaMA / ChatGPT) to extract and classify GDPR sanctions from CNIL reports; packaged as a production Streamlit app for compliance teams with model versioning and basic monitoring. Included data preprocessing, evaluation, and human-in-the-loop validation. Tech: LLaMA, OpenAI APIs, Python, AWS SageMaker, Streamlit, Docker..
- Designed and delivered ETL workflows and ingestion for competitor monitoring Tech: Scrapy Playwright, AWS Sagemaker jobs, BigQuery, Streamlit, pytesseract), reducing data latency to near real-time
- ITG ConsultantsB2B Data Analyst (free-lance)INGÉNIERIE MÉCANIQUEjanvier 2018 - février 2022 (4 ans et 1 mois)Paris, France
- Led data quality, enrichment, and optimization initiatives for account targeting based on technographic and firmographic criteria → Delivered ICP modeling for clients such as Wedia, BirdOffice, and PG Organisation in collaboration with Eleius Marketing
- Conducted digital performance benchmarking across global markets for clients including Michelin Group (TyreDating) and Prevision.io → Identified optimization levers through comparative analysis and positioning diagnostics
- Designed and implemented client segmentation models to improve targeting, messaging, and commercial alignment → Supported strategic pivots for companies like Qonto and Disruptive Innovation Group, via classification models and actionable scoring matrices
- GL eventsData Marketing Manageravril 2005 - septembre 2017 (12 ans et 5 mois)Lyon, FranceStrategic Project Support: Provided data-driven support for large-scale tenders and international events: World Expo, FIFA World Cup, etc. •
- Led data collection, market intelligence, and competitive analysis to guide strategic positioning and proposal writing
- Developed custom scraping workflows to extract and structure high-volume unstructured data (press, web, tender databases)
Marketing Insight Automation & Scalable Tools : •- Automated the generation of marketing insights for event benchmarking, enabling effective segmentation, targeting, and opportunity scoring for commercial teams
- Designed and implemented a search engine scraping over 10 million web pages per year, adexing event data by industry sector, region, and performance metrics (tool used to respond to +500 web-based data requests annually, significantly improving commercial responsiveness)
Acted as a key interface between business stakeholders and external data providers, ensuring strategic relevance and data quality across all initiatives.
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Formations
- Concepteur développeur en sciences de donnéesJedha20221-Construction et alimentation d'une infrastructure de gestion de données (scraping, AWS, cartographie) 2-Analyse exploratoire, descriptive et inférentielle de données (data visualisation) 3-Analyse prédictive de données structurées par l'intelligence artificielle : machine learning supervisé (prédiction / classification / clusterisation par Kmeans et DBScan) 4-Analyse prédictive de données non-structurées par l'intelligence artificielle (NLP : Modèles de deep learning séquentiels et transformers) 5-Industrialisation d'un algorithme d'apprentissage automatique et automatisation des processus de décision 6-Direction de projets de gestion de données : rétroengineering des facteurs de ranking sur Google
- The Hacking ProjectThe Hacking Project2017Bootcamp de développement sur Ruby on Rails : HTML, CSS, Javascript
Certifications
- Data SEO LAb Niveau 1Data SEO LAB