Description

ML Engineer - ML Ops

With solid experience at Solocal and Renault Digital, I specialize in applying data science to digital marketing.

I build, evaluate, productionize, and optimize Machine Learning models to effectively enhance project performance, especially using Google Cloud Platform (but open to others).

Additionally, I lead data science teams, fostering a collaborative and innovative environment.

How can I help you ?

Industry field of expertise

Languages

French
Native or bilingual
English
Native or bilingual

Workplace preferences

Can work on-site

Montpellier (up to 20km), Lyon (up to 10km)

Solocal SA
ML Ops
SOFTWARE PUBLISHING
October 2021 - Today (4 years and 9 months)
Boulogne-Billancourt, France
Built a robust MLOps framework around the search ranking algorithm, integrating comprehensive tests, rigorous data validation, and orchestration, which improved pipeline automation, reduced deployment times by 50%, and debugging time by 60 - 80%.

Developed and iteratively refined Media Mix Modeling inside an ML Ops framework for client ads. Introduced Bayesian Inference with MCMC into the pipeline with LightweightMMM.
Actively contributed to the Data Science team through detailed research article and book summaries, knowledge-sharing workshops organisation. I also drove the democratization of data science across the company, bringing data literacy and collaboration to 5 different departments.
Marketing Mix Modeling Python Google cloud ChatGPT LLMs Gitlab CI/CD Docker Terraform
Renault
Data Scientist
AUTOMOBILE
September 2019 - October 2021 (2 years and 1 month)
Boulogne-Billancourt, France
Maintenance and Optimization of Industrialized Machine Learning Models

Creation and Industrialization of an End-to-End Machine Learning Pipeline to Predict Customer Affinity for a Car Model
Leveraging Google Analytics Data to Retarget High-Potential Customers
Google cloud Python SQL Gitlab CI/CD Scikit-learn