Simon Lemieux
Power BI Developer at RMC - Risk Management Certification
Greater Montreal Metropolitan Area Canada
Summary
👤
Senior🎓
Top SchoolSimon Lemieux is a Power BI developer and seasoned finance professional with 16 years of cross-industry experience combining advanced data engineering, ML-aware back-end contributions, and deep corporate finance expertise. He currently builds analytics solutions at GIRO while teaching finance and risk management at HEC Montréal, where he earned a recent pedagogical excellence award—an uncommon blend of practitioner and educator. Proficient in Power BI, SQL, R, MATLAB and VBA, he has driven BI platform migrations, automated reporting that shrank reporting footprints dramatically, and delivered data-driven market insights for brands like L’Oréal. His background in investment analysis and CFA-level training underpins rigorous financial modeling, valuation and risk work, complemented by contributions to the MLDB open-source project focused on text processing and dataset merging. Trilingual in French, English and Spanish, he thrives at the intersection of quantitative finance and practical business intelligence, turning complex datasets into strategic decisions.
16 years of coding experience
1 year of employment as a software developer
International Exchange Finance, International Exchange Finance at University of DeustoM.Sc. Finance Finance General, M.Sc. Finance Finance General at HEC Montréal
French, English, Spanish
Stackoverflow
1,119reputation
587kreached
33answers
3questions
Github Skills (13)
text-processing10
data-analysis9
python9
machine-learning9
sql8
git7
wave6
json6
javascript6
tensorflow6
numpy6
serialization6
django6
Programming languages (11)
Github contributions (5)
mldbai/mldb
Jan 2016 - Mar 2017
MLDB is the Machine Learning Database
Role in this project:
Back-end Developer
Back-end DeveloperContributions:106 commits, 44 PRs, 102 pushes in 1 year 2 months
Contributions summary:Simon primarily contributed to the development of the Machine Learning Database (MLDB), focusing on backend functionalities. Their work involved fixing typos in the documentation, implementing changes to stemming algorithms, and adding tests for sum(stemmer(tokenize(...)) use cases. The user also worked on merging branches and enhancing the dataset merging functionalities, showcasing a focus on improving the MLDB's text processing and data analysis capabilities.
pythonmachine-learning-databasedata-sciencemachine-learningdatabase
simlmx/.dotfiles
Aug 2012 - Jan 2023
Contributions:132 commits, 48 pushes, 1 branch in 10 years 6 months
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