About Nicolas
With a master of science degree in engineering and a specialization in data science from Telecom ParisTech, Nicolas has been solving concrete business cases for three years using machine learning and data mining. His experience in the eCommerce, banking, and consulting sectors give him a very strong technology portfolio and a deep understanding of different business types.
French
Native or bilingual
English
Native or bilingual
Portuguese
Fluent
Can work on-site
Paris (up to 50km)
Experience
- RappiData Scientist for Product CategorizationE-COMMERCEJuly 2020 - December 2020 (5 months)- Developed a product categorization model from scratch using machine learning and Python to automatically classify products from the ecommerce application on three levels of granularity (the level two and three give a more detailed categorization than level one).- Assigned the model to automatically classify four million products sold in the company’s eCommerce application in eight different countries in Latin America in 400 different categories (from fresh food like fruits or meats to beauty products).- Put into production this model to be run automatically when onboarding new products.- Developed a matching tool using natural language processing to match new onboarding products to products already existing in the catalog of the eCommerce application (to use standard information from products already verified from the catalog).
- WavestoneData ScientistCONSULTING AND AUDITSMarch 2017 - August 2017 (6 months)- Created a Predicitive Maintenance model for a transport company using Machine Learning (data cleaning, Gradient Boosting Trees and detecting very rare events).- Created a benchmark of text classification methods with the purpose to develop a chatbot for the company.- Crunched and analysed data for a French national social organism to detect loss of money in allowances distribution.
- CDISCOUNTData Scientist specialized in Credit Risk ScoringE-COMMERCEOctober 2017 - December 2018 (1 year and 2 months)Bordeaux, France- Designed and developed an accurate, useful, and stable credit risk model for payment in four installments on the company's selling platform.- Initiated the production of new, improved credit scoring models every three months.- Optimized credit scoring models to score in real-time every customer buying on the website (1 million visits per day, implied building a very fast computing model).- Integrated new data sources and solutions into credit risk strategies.- Interpreted data science models and gave business recommendations to senior leaders.
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Education
- Master of Science in Engineering (speciality Data Science)Telecom Paristech2017Courses of Machine Learning, Deep Learning, Statistics and Programming.