Simon Ouellette is a seasoned AI tech lead and machine learning specialist with a decade of experience building real-world solutions in time series, reinforcement learning, computer vision, and deep learning, based in Montreal, Canada. As AI Tech Lead at Trabotyx since 2025, and formerly Senior ML Engineer there, he combines hands-on engineering with strategic leadership across AI initiatives and production systems. He has a strong record of open-source contributions, notably enhancing the spark-timeseries library with a flexible lagging API and robust tests, expanding analytics capabilities on Apache Spark. His career spans founder/consulting roles and senior ML positions (Pointus Partners, Faimdata, Nabla Analytics) including algo-trading work, data architecture, and enterprise analytics, reflecting a broad, cross-domain toolkit. He holds a Master's in Computer Science with an AI specialization from Université du Québec à Montréal and maintains a personal website at simonouellette.com, bridging rigorous research with production-scale impact.
A library for time series analysis on Apache Spark
Role in this project:
Back-end Developer
Contributions:44 commits, 8 PRs, 105 comments in 2 months
Contributions summary:Simon primarily focused on enhancing the `spark-timeseries` library for time series analysis on Apache Spark by implementing new functionality and improving existing code. Key contributions include exposing a new `lag` function for time series lagging, fixing bugs in the lagging implementation, and adding unit tests to ensure correctness. The user also introduced a more flexible `lags` function that allows for custom lagging configurations per column, significantly expanding the library's capabilities.
Contributions:16 commits, 13 pushes, 1 branch in 1 month
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