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Greater Paris Metropolitan Region

Data Consulting Firm specializing in various sectors, including energy, healthcare, industry, and services.Key Responsibilities:---------------------- ---> Conducted data analysis and modeling using Python and R. ---> Managed data throughout its lifecycle. ---> Developed Computer Vision models. ---> Engaged in Research and Development projects in data.

Greater Rennes Metropolitan Area

As a Teaching Assistant for practical and tutorial sessions in Machine Learning, I supported students in understanding core concepts and applications of machine learning algorithms. My responsibilities included: ---> Assisting in the preparation of course materials and assignments to reinforce theoretical knowledge through practical application. --->.

Montrouge, Île-de-France, France

Development of a Data Orchestration, Qualification, and Validation ApplicationContext:-------- ---> Design and develop an application to orchestrate data flows, ensuring the qualification and reliability of measured data. ---> Collaborate with cross-functional teams to optimize data integration and processing workflows. ---> Provide ongoing application.

La Défense, Île-de-France, France

Consultant for the Financial Directorate - Development of a Web Application Suite for Data Flow Monitoring and Energy Forecast Quality ControlKey Taks:---------- ---> Redesign and rewrite an existing R Shiny application to create a comprehensive ecosystem of R Shiny applications. ---> Develop R Shiny modules for monitoring data flows, tracking model.

Palaiseau, Île-de-France, France

Consultant for the R&D Department - Development of an Algorithm for Medium/Long-Term Forecasting of Electrical Load TrendsKeys Tasks:------------ ---> Conducted an in-depth analysis and diagnostic of the previous forecasting method. ---> Cleaned and analyzed time series data of electric load from source substations. ---> Proposed and implemented a trend.

Montigny-le-Bretonneux, Île-de-France, France

As a data scientist in an R&D team, I focus on validating Generative Adversarial Network (GAN) discriminators for mechanical design by quantifying uncertainty in deep neural network predictions. My work employs Bayesian inference methods in deep learning, primarily using images as data.Key Responsibilities:---------------------- ---> Developed deep.

Semantic Address Matching and AnalysisKey tasks:----------- ---> Automated the extraction of information from postal addresses using Deep Learning (NLP, NER) and Hidden Markov Models. ---> Developed an address matching algorithm with the BD TOPO database using a vector-based database with FAISS. ---> Built a web application with Flask to deploy the.

Proposed an effective process for analyzing the impact of treatments.Key tasks:----------- ---> Identified the limitations of using p-values in statistical analysis. ---> Analyzed the prevalence of the hepatitis E virus in pig farms at slaughter age. ---> Implemented bayesian techniques to assess the practical significance of comparison tests.

Redesigned the retail credit score for leasing.Key tasks:----------- ---> Selected and discretized of variables using decision trees. ---> Built scoring models using logistic regression and XGBoost with SAS and R. ---> Developed a scoring grid to evaluate and classify risks more effectively. ---> Improved the bank's scoring model's discriminating power by.

Cotonou, Littoral, Benin

This is an academic internship at the Department of Statistics and Economic Studies of the National Institute of Statistics and Economic Analysis of Benin. It was carried out as part of my bachelor's degree in Statistics and allowed me to produce my final dissertation on the topic: Gross Domestic Product and Electrical Energy in Benin: a causality.

Engineer'S Degree, Data Science And Data Engineering

Economist Statistician Engineer, Statistics And Economics

Activities and Societies: Pool Informatique, ISSEA English Club

Bachelor Of Applied Science - Basc, Economical And Sectorial Statistics