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Création de jobs de webscrapping
Classification de données textuelles via des techniques de
NLP
Design et rédaction de use case d'un outil de veille
concurrentiel
Python, R
* Used logarithmique regression to predict the charge of each post office.
* Automatised the process to only use a python script.
* Wrote a documentation on the methodology used.
* Research and convert information from raw data into an easily understandable analysis that identifies trends and insights of the different ways Belfius' customers are investing and saving.
* Trained unsupervised clustering algorithm such as kmeans and Hclust in order to provide a new segmentation that highlights the behavior associated to each way of saving. Used nlp to classify transaction's label.
* Run machine learning experiments and tested several algorithm such as random forest, xgboost, logistic regression, SVM, k-means and others in order to build a fraud detector. Provided advice to the data science team reagarding the use of Dataiku by anwswering the questions and showing how to properly use the tool.
* Implementation of a fraud suspicion ladder.