Francois Werbrouck

I build and maintain data pipelines enabling efficient extraction and analysis for AI powered solutions. I develop scalable data infrastructure solutions and AI agents to generate business insights and streamline processes.

This role that has given me the opportunity to work at the intersection of data analysis, machine learning solutions, and real business impact. During this final internship, I've had the chance to: - Lead the full lifecycle of an ML-driven data application from proof of concept to production, covering system design, development, testing, and client presentations, all built on Databricks. - Build an ETL pipeline leveraging web scraping technologies answering various business demands. One of which included the automation of fetching invoice. This replaced a manual process with an automated pipeline that fetches, parses, and now loads invoice data directly into our Databricks infrastructure. This now powers spending reports and analysis that directly support strategic business decisions. Working closely with stakeholders has reinforced how much my impact depends on understanding the business problems behind the data, but also how much it can assist business representative in their day to day tasks.

In charge of the MLOps for the R&D Lab. The objective of my internship is to transition the lab's project on a Databricks infrastructure to better manage the lifecycle of each project in a centralized environment.

Ai-Lab team - https://github.com/ai-cfia/ailab-datastore/

I was managing various system and software for our in house solutions. I was the first point of contact with various client across the agency analysing their needs and the data provided. I was maintaining various database and macros that were pivotal for the workflow of the agency.