Sebastián Saaibi
VP Of Engineering at treble.ai
Old Toronto, Ontario, Canada
Summary
👤
Senior🎓
Top SchoolSebastián Saaibi is a VP of Engineering and machine learning practitioner with 16+ years applying ML to marketing, commerce, healthcare and finance, currently scaling engineering at Treble.ai to drive conversational CRM growth via WhatsApp. He has a track record of building data teams and shipping production ML products from startups to hyper-growth companies—having led and expanded data organizations at Shopify, Phreesia, Pager and his own studio Baisano Labs. Sebastián blends hands-on modeling and product thinking (“I brew data”) with leadership: hiring, mentoring, and creating cross-functional analytics and ML platforms that power merchant-facing analytics and cohort, categorization and causal-insight systems. His background spans academia and quantitative research (ETH Zürich, Harvard fellowship, econophysics and trading strategy R&D), which informs a rigorous, experiment-driven approach to product metrics and model validation. Based in Toronto, he uniquely combines deep computational training and practical product delivery, often translating complex models into simple data-driven features for non-technical stakeholders.
11 years of coding experience
13 years of employment as a software developer
MSc Computational Science and Engineering (RW), MSc Computational Science and Engineering (RW) at ETH ZürichUniversidad de los Andes
English, Spanish, German, Portuguese, French
Stackoverflow
452reputation
48kreached
14answers
2questions
Github Skills (40)
del10
python9
airtable9
r-api9
whiteboard8
database8
deep-learning8
slack8
tensorflow8
machine-learning8
visualization8
r8
postgresql7
mysql7
neural-network7
Programming languages (7)
Github contributions (5)
spsaaibi/spsaaibi.github.io
Jan 2016 - Jan 2018
Contributions:4 PRs, 41 pushes, 5 branches in 2 years
data-analysispythonsciencedata-sciencemachine-learning
spsaaibi/baisano
May 2019 - Jul 2021
Baisano Labs
Contributions:2 PRs, 20 pushes, 2 branches in 2 years 2 months
kubernetes
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