Marco Peixeiro
Applied AI Scientist at Nixtla
Saint-Bruno, Quebec, Canada
Summary
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Rockstar🎓
Top SchoolMarco Peixeiro is an Applied AI Scientist with nine years of experience building NLP-driven customer service automation and time series forecasting solutions, currently at Nixtla. He designs and deploys chatbots, Q&A systems, and optimized search using transformers and embeddings, and has led scientific experiment planning, conference presentations, and peer review activities. Previously a Senior AI Scientist at National Bank of Canada, he also created a company-wide data science academy to upskill employees and improve retention while delivering credit-modeling ML systems. An active technical educator and author, Marco publishes on Towards Data Science, creates Udemy courses, and is writing a 21-chapter book on time series forecasting whose companion GitHub repository showcases practical forecasting code and visualizations. Comfortable bridging research and production, he pairs deep Python/TensorFlow/PyTorch expertise with full-stack development experience from earlier roles.
9 years of coding experience
6 years of employment as a software developer
DEC Sciences de la santé, DEC Sciences de la santé at Vanier CollegeNanodegree Artificial Intelligence, Nanodegree Artificial Intelligence at UdacityBachelor's degree Génie chimique, Bachelor's degree Génie chimique at McGill University
French, English, Spanish, Portuguese
Github Skills (11)
data-analysis10
scikit-learn10
data-visualizations10
pandas10
time-series10
data-visualisation10
data-visualization10
python10
statsmodels10
numpy10
scikit10
Programming languages (4)
Github contributions (5)
marcopeix/TimeSeriesForecastingInPython
Jul 2021 - Dec 2022
Role in this project:
Data Scientist
Data ScientistContributions:46 commits, 39 pushes, 1 branch in 1 year 5 months
Contributions summary:Marco's commits primarily involve implementing and updating code for the first chapter in a time series forecasting in python book. The code involves using libraries like pandas, numpy, matplotlib, statsmodels, and scikit-learn to visualize, decompose, and model time series data, specifically focused on time series analysis and demonstrating time series forecasting techniques. Based on the commit messages and code examples, the focus is primarily on data manipulation, visualization and applying models.
marcopeix/datasciencewithmarco
May 2020 - Sep 2022
All notebooks from video tutorials
Contributions:19 commits, 21 pushes, 1 branch in 2 years 3 months
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