Vincent Barnabé-lortie
Data Science Team Lead - AI In Commercial And Specialty Lines
Montreal, Quebec, Canada
Summary
👤
Senior🎓
Top SchoolVincent Barnabé-lortie is a bilingual data science leader in Montreal with 13 years of experience combining software engineering, ML/AI, and product delivery, currently heading AI for Commercial and Specialty Lines at Intact. He has a proven track record shipping production GenAI solutions and reusable RAG designs that cut information-search time by over 50% and accelerated time-to-market for related products from months to weeks. Comfortable bridging research and operations, he has scaled teams, written system‑level AI and ethical reviews, and used Bayesian models to validate business impact and enable real-time KPI dashboards. His background spans startups and media—where he deployed recommendation systems at scale—and includes impactful open-source contributions to papermill, adding Azure Data Lake and Julia kernel support. Vincent pairs an MBA with an MCS and software engineering roots, bringing both strategic, cross-functional leadership and hands-on engineering depth.
13 years of coding experience
11 years of employment as a software developer
Master of Business Administration - MBA, Master of Business Administration - MBA at McGill University - Desautels Faculty of ManagementMCS Computer Science, MCS Computer Science at University of Ottawa
French, English, Chinese
Github Skills (9)
parameterization10
notebook10
python10
julia10
pytest9
pipeline9
testing9
unit-test9
unit-testing9
Programming languages (3)
Github contributions (5)
nteract/papermill
Aug 2018 - Jun 2019
📚 Parameterize, execute, and analyze notebooks
Role in this project:
Back-end Developer & Cloud Engineer
Back-end Developer & Cloud EngineerContributions:20 commits, 8 PRs, 19 comments in 9 months
Contributions summary:Vincent primarily contributed to the integration of Azure Data Lake (ADL) support, enhancing the data source and sink capabilities within the papermill library. They developed ADL-specific handlers and tests. Furthermore, the user added Julia language support, including translators, which expanded the library's ability to parameterize notebooks across different kernels. This involved significant changes to the core infrastructure of the library.
nteractpublishingpythonpipelinedata-science
VincentBLortie/papermill
Aug 2018 - Jun 2019
📚 Parameterize, execute, and analyze notebooks
Contributions:25 pushes, 9 branches in 9 months
pythondata-sciencejupyter-notebooknotebookparameterize
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