Rémi Canard
Group Product Manager, Performance & Lead Of Issuer Partnerships at Checkout.com
London, England, United Kingdom
Summary
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Rockstar🎓
Top SchoolRémi Canard is a Group Product Manager with 10 years’ experience combining technical rigor in computer science and data science with deep domain expertise in online payments and optimization. At Checkout.com he built and scaled the Payment Performance organisation from data-science roots to a 20‑person product and engineering team, shipping Intelligent Acceptance and other initiatives that recovered millions in merchant revenue. He excels at translating complex payment flows and ML-driven recommendations into pragmatic product roadmaps, go‑to‑market strategies, and cross‑functional programmes involving issuers, schemes and merchant partners. Known for hands‑on data fluency, he moves fluidly between modelling, engineering trade-offs and stakeholder communication to find high‑impact opportunities. Based in London, he combines startup agility from his ProcessOut days with enterprise execution at Checkout.com, and is committed to continuous learning and team development.
10 years of coding experience
7 years of employment as a software developer
Classes Préparatoires aux Grandes Ecoles – Scientifique, Classes Préparatoires aux Grandes Ecoles – Scientifique at Lycée Laetitia BonaparteMaster's degree, Computer Science & Business Intelligence, Master's degree, Computer Science & Business Intelligence at EFREI - Grande école du numériqueMaster's degree, Data Sciences & Business Analytics - joint degre, Master's degree, Data Sciences & Business Analytics - joint degre at ESSEC | CentraleSupélec - Master Data Sciences & Business Analytics
French, English
Github Skills (9)
algorithms8
statistics8
python8
data-science7
data-analysis7
machine-learning7
jekyll6
scikit-learn5
github-pages5
Programming languages (1)
Github contributions (5)
remicnrd/DS_moocs
Dec 2015 - Jul 2017
Contributions:26 pushes, 3 branches in 1 year 7 months
remicnrd/ml_cheatsheet
May 2018 - May 2018
A 5-pages only Machine Learning cheatsheet focusing on the most popular algorithms under the hood
Contributions:8 commits, 7 pushes, 1 branch in 1 day
machine-learning
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