À propos de Nathan
Senior Data Analytics professional with experience across consulting and industry. Specialized in data visualization, automation, and machine learning, with strong expertise in Python, NLP, and BI tools (Power BI, Tableau). Proven track record of building end-to-end data solutions—from data engineering and KPI development to deploying ML models with Docker and Flask—to drive performance improvement and strategic decision-making.
Français
Bilingue ou natif
Anglais
Bilingue ou natif
Accepte de travailler sur site
Paris (jusqu’à 30 km)
Expériences
- StmicroelectronicsBusiness AnalystINDUSTRIE MATIÈRES PREMIÈRESdécembre 2023 - janvier 2026 (2 ans et 1 mois)Singapour, SingapourGoal: Help the Purchasing Team to improve its performance- Designed and automated spend analysis dashboards (Power BI | Power Automate)- Built a supplier performance dashboard to help buyers to negotiate and reduce cost (Power BI)- Developed programming scripts to clean and consolidate procurement data from SAP (Python)- Trained team members on data visualization and self-service analytics tools, improving cross-functional collaboration (Power BI)
- Sia PartnersData Analytics ConsultantCONSEIL & AUDITjuillet 2020 - novembre 2023 (3 ans et 4 mois)Paris, FranceGoal: Monitored the Enedis performance & client satisfaction- Framed the business need (workshop, sketch)- Developed backend (Python | Oracle | SAS | Airflow): calculated and integrated several KPIs- Developed and maintained a dashboard (Tableau | PowerBi)Goal: Developed an automated summary generation model for Total- Benchmarked the best models (extractive and abstractive)- Developed and optimized the NLP summary generation model (LexRank | DistilBart)- Post-processing: developed an algorithm for recovering lost key terms (Spacy)Goal: Developed a tool to analyze business E-reputation thanks to press articles- Web scrapping: Developed an automated article retrieval module (Selenium | BeautifulSoup)- Developed a semi-supervised model to label texts: keywords detection (KEYBERT), Word2Vec embedding, similarity calculation (cosin, Levenstein)- Developed an entity detection model (NER Spacy)- Developed a classification model (Transformers XLM Roberta)- Deployed solution (Docker | Flask | Dash)
- LaunchmetricsData ScientistMODE & COSMÉTIQUESjanvier 2020 - juin 2020 (5 mois)Paris, FranceGoal: Developed an NLP model to deal with ambiguous brand names (ex: Céline, Chloé, Total…)- Data Engineering (AWS | Python | Git)- Data Analysis (Python: Pandas | MatplotLib)- Created and optimized an NLP classification model (Bi LSTM | DistilBERT)- Deployed an API model (Flack | Docker)
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Formations
- Ingénieur spécialisé en Data ScienceArts et Métiers ParisTech2020Python | Linux | Machine Learning | Power BI & Tableau Software | SQL | Django & Flask | Docker
Certifications
- Data Analysis with PythonCoursera2020
- Data Visualization with PythonCoursera2020