About

Who Am I?

Welcome! 👋

Currently working as Data Analyst at YesWeHack, I often use Dataiku DSS, Apache Superset, Python and SQL.

I used to report my works and thinking here. You will find several articles about d3.js (which is awesome for data visualization), machine learning and a lot of interesting topics related to data.

Children’s education in the world is one of my main motivation in life.

Do not hesitate to reach me by mail or LinkedIn. It would be a pleasure for me to chat with you.

Resume

(click on toggles to get details)

Skills

Python : Numpy, Matplotlib, Pandas

Tensorflow, Pytorch, Scikitlearn

Django, Flask, SQL

Data visualization: Seaborn, D3.js, Plotly, Dataiku DSS, Apache Superset

R, Javascript

Agile method

Oral and written restitution of results

Experiences

Data Analyst, Yes We Hack | Since 2023

Data & Operations Engineer, Morpho Labs | 2022-2023 (1.5 years)

Development of a cash flow monitoring automate process

Designing of a financial and accounting stack

Consulting in Data Science, Freelance | Since 2018

Web data extraction for price analysis

Development of a price comparison system for e-commerce

Data Scientist, DATASWATI - BCG | Spring 2019

Waste prediction on a production line

Predictive modeling for industrial process

Code review and performance analysis

Pipeline development for computer vision

Education

Engineering Degree, Télécom Paris | 2019-2023

Data Science and Economics

Statistics, Data Analysis, Data Mining, Databases, Machine Learning, Microeconomics, Econometrics.

Bachelor's Degree, Université Paris Saclay | 2016-2019

Science and Technology

Interdisciplinary and Project Based Learning.

Computer Science, Engineering, Maths, Physics, Chemistry, Biology.

High School Diploma, Lycée Réaumur | 2016

Engineering Science

Specialty: Computer and Digital Science

Projects

Conception of a Sparse Neural Network

Method used in embedded systems

Data analysis and application in different network architectures

Visualization of error rates

Project management (team of 4 people)

Kaggle Competition: Breast Cancer Prediction

Data cleaning and mining

Identification of influential features

k nearest neighbor algorithm implementation with 99% accuracy

Technologies used: Python, Scikit-Learn (KNN), Pandas, Seaborn, Git, Jupyter Notebook.

Bike Sharing Prediction

Creation of a temporal prediction model for the use of a bike sharing service in Washington

Comparison of models and selection based on performance

Management of a team of 3 people

Technologies : Python, Scikit-Learn, Matplotlib.

Guessmynumber.com

Recognition of a number drawn on a web page

Ultra-fast client-side recognition

Technologies: TensorFlow, Django, Bootstrap, Heroku

Commitments

Humanitarian Project in Sri Lanka | August 2019

Educational, material and moral support for war orphans in Jaffna.

Presidency of the Edukids association.

Humanitarian Project in Burkina Faso | February 2018
With the NGO LTGA, in order to make a school self-sufficient in energy with solar panels