Description

I worked as a data scientist at Reezocar. I developed skills to lead projects from ideas to production. Data analysis, machine learning and when necessary deep learning. The last few years I moved onto data engineering and data architecture in general.

Recently I've had an interest in the AI capacity to generalize the understanding of a problem and the ARC (Abstraction and Reasoning Corpus) challenge specifically.

Languages

French
Native or bilingual
English
Fluent
Spanish
Basic

Workplace preferences

Remote only

Primarily works remotely

SAS Check&Visit
R&D / Data Engineer
REAL ESTATE
September 2020 - Today (5 years and 9 months)
Data Engineer

Machine Learning - Deep Learning - Mobile integration of DL models - REST API - Serverless - Data Architecture
Machine learning Deep Learning API REST FastAPI GraphQL Serverless Docker docker-compose
Reezocar
Data Scientist
AUTOMOBILE
July 2017 - July 2020 (3 years)
Paris, France
Machine Learning - Deep Learning - Image Processing - Natural Language Processing - Data Analysis - Recommender System - Lambda Architecture - Azure Datalake

The mission of Reezocar is to facilitate the research and to secure the purchase of second-hand cars in Europe. To that end, Reezocar gathers millions of second-hand cars ads.

The Data Science team has multiple missions :
- Ensure data quality and availability
- Design solutions to business issues based on data modelling
- Develop, deploy and maintain these solution

Examples of projects deployed include :
- NLP matching algorithm (based on Microsoft publication) to extract information from unstructured products.
- Recommender system to match the best products based on a client project
- Prediction of market value variation
- Image processing for classification and filtering
- Design and implementation of an Hadoop-based Datalake with 500M+ documents to meet the Data Science Team needs

Technologies : Python, Numpy, Pandas, Scikit, Graphql, Hadoop, Hive, Spark, Data Factory, ElasticSearch, SQL, MongoDB, Redis, Azure, Jenkins, Git, Docker, Kubernetes, etc
Python Kubernetes GraphQL Jenkins Microsoft Azure MongoDB Redis Docker Elasticsearch Scikit-learn Pandas Numpy Hadoop Hive MySQL
Pumpkin App
Data Scientist
BANKING AND INSURANCE
September 2016 - June 2017 (9 months)
Paris, France
The FinTech world is on the edge of revolution. These fast growing companies aim at a better quality of service along with a more stable financial landscape. Built on the merging of financial services and communications technology, these companies go from payments to wealth management, crowdfunding to peer-to-peer lending.

Pumpkin is one of the main actors in the french FinTech with fast growing community. Pumpkin app is a simple and secure mean of payment among friends. Pumpkin is drove by the conviction that paying a friend should be as simple as sending a text. I was in charge of developing a deeper knowledge of the database to improve decision making.

• Multi-scale reports
• Data dashboards & templates for specialized team
• Activation & retention strategy
• Automate data refresh & standalone reports
• Mini-Websites development

--- Technical skills ---
• DAX, powerBI (Microsoft)
• Python Scientific & Analytic packages (Pandas, NumPy)
• Web development (HTML, CSS, Javascript, PHP)
• Matlab

--- Human skills ---
• Efficiency & Productivity
• Synthetic thinking
Python Microsoft Power BI HTML5 JavaScript PHP