Rhizlaine DEGNI | Enthusiastic Data Scientist

Rhizlaine DEGNI

Enthusiastic Data Scientist

Based in Lyon, France

About

A Junior data scientist with a 6 months experience in Computer Vision and problem solving for a start-up specialised in marketing and social networks.

Skills

Projects

Climate events in the United States in 2017

Using a dataset on climate events in the US in 2017 to try to correlate the damage caused by natural disasters in the United States with the price of home insurance. But also, we can establish a temporal visualization of event occurrences to determine on which seasons each type of event...

Twitter Sentiment Analysis: Hate tweets recognition

In recent years, the increasing propagation of hate speech on social media and the urgent need for effective countermeasures have drawn significant investment from governments, companies, and researchers. The objective of this task is to detect hate speech in tweets. For the sake of simplicity,...

Image Moderation

Content is of prime importance for any advertising as it is what consumers are attracted to and engage with. Digital out of home advertising displays allow you to present dynamic and creative content. You can aggregate, moderate, and display user-generated content as part of your digital out of...

Experience

2019

Data Scientist Intern

Addressing the need for image moderation for social media advertising through the use of a CNN. Creation of the dataset and labeling using the ELO algorithm through a voting system with a Slackbot to limit biases. Creation of a Chrome plugin as a userscript for image retrieval on Twitter and Instagram and their storage in an AWS S3. Transfer learning from DenseNET201 on an EC2. Sensitivity of beautiful images: 95%, specificity of other images: with an RMSE of 0.08 on the "beauty" score of the images.

2022-now

DevOps Automation Engineer

As a DevOps Automation Engineer, I contributed to the implementation of automation solutions using DevOps practices. This involved using my skills in Ansible, AWX, CI/CD, Azure DevOps, and Python to develop and improve systems that streamlined processes, reduced errors, and saved time. To support these efforts, I utilized my Python skills to develop custom scripts and tools for automating various tasks and improving overall system performance.