Luc Sim

Background

About Luc Sim

I am Luc SIM and I am passionate about Data Science. I have skills in data analysis, data visualization, machine learning and generative AI. I am looking for a new job in data science in France or abroad. I am currently working at Bouygues Télécom. My first task was to modelize the risk of a mobile fraud, for that I used Machine Learning algorithms with Dataiku. It was pushed in production and the predictions could be monitored with a Tableau dashboard. Right now, I am developping a generative AI with Dataiku/Prisme AI to help people in the company find their reporting and understand how to use it. My previous mission was at Orange (France leader in telecom) as a Data Scientist, and using Data Science to improve the understanding of their profesional customer chatbot. I am also using Machine Learning models and BERT for mail classification and data anonymization. I also worked as a Data Scientist/ Data Engineer for IDEX, a french energy provider. The objective was to setup a Dataplatform on the Microsoft Azure cloud that will centralize all of IDEX's Data. To valorize this data, I have created various pipelines for computing KPI, doing Machine Learning to predict gaz consumption. I did my end of studies Internship at Orange Applications for Business. I worked on several missions that allowed me to use my Python programming skills, my data mining skills and machine learning skills (Supervised and unsupervised learning). My previous internship was at Safran Aircraft Engines, within the DATALAB Team. I have conceived and deploy a web application for data vizualisation. I could enhance my skills in Python programming, databases management and deploy the app on a Linux server. I also worked on a project with Qwant, a european search engine. I did data modelisation, crawling and text mining with Python. I also studied at the University of New Mexico (USA) during the fall semester of 2017. In my Machine Learning class, I particpated at Kaggle competitions that allowed me use different algorithms such as Random Forests, Logistical Regression, Naive Nayes and Neural Networks.