Senior Data Scientist
2019 - PRESENTFreelancer- Developed a propensity scoring system using ML for an application for runners. The goal was to predict which free user bases where more likely to convert and when—to help them target email marketing communications.
- Created a system that reads grocery invoices and detects the products and the banner at which the purchase was made for a couponing company using the Google Cloud AI's Vision and Natural Language APIs with the Python SDK.
- Performed CLV predictions and segmentation using CRM data at a US-based hotel chain resulting in the retention of high-value guests using Python and Scikit-learn.
- Built a machine learning-based system predicting the real estate value of more than two million properties in Canada with XGBoost.
Technologies: Python, SQL, Machine Learning, Data Analytics, Data Science, Google Cloud Platform (GCP)Data Scientist
2017 - 2019JLR Solutions Foncières- Developed, integrated, improved, and maintained a machine learning model able to estimate the market value of the houses in Canada with LightGBM in Python and SQL for the ETL process.
- Built a housing price index based on the three-stage least-square regression methodology by Case and Shiller (1987) using Python and SQL Oracle.
- Wrote reports on the state of the real estate market. Produced econometric analyzes based on real estate microdata. Communicated the analysis produced from the data and was interviewed on radio and newspapers about these studies.
Technologies: Python, R, Machine Learning, Data Analytics, Data Science, Google Cloud Platform (GCP)