Margot Brard-besnard
Prod Lead Team Leader at ThinkR
Rennes, Brittany, France
Summary
👤
Senior🎓
Top SchoolMargot Brard-besnard is a product-focused data scientist and team leader with nine years of experience bridging product, data, and delivery across consultancy and R-centric engineering roles. Based in Rennes, she has moved from sensometric research (PhD) into industrial data projects and now leads product and operational performance at ThinkR, combining hands-on R development, CI/CD and cloud deployment with project strategy and sales support. She coaches and scales teams through standardisation, visual management of performance and continuous improvement, while still contributing to package development, testing and reproducible workflows. Comfortable translating complex statistics into production-grade solutions, she uniquely pairs academic rigour in sensory data with practical product leadership and a passion for R tooling.
9 years of coding experience
4 years of employment as a software developer
Master, Applied statistic, Master, Applied statistic at Université Rennes 2Doctor of Philosophy, Statistic and modelisation for the food industry, Doctor of Philosophy, Statistic and modelisation for the food industry at Life-Agronomy-Health doctoral schoolEngineer, Food science - Major: Applied statistic, Engineer, Food science - Major: Applied statistic at L'Institut Agro Rennes-AngersLean Manager, Lean Manager at Learning to Scale
English, Spanish
Github Skills (26)
r-package9
prepare9
shiny-apps8
shiny8
rshiny7
r7
css7
gitlab7
api6
clustering5
regression5
gitlab-api4
package4
modeling4
modification3
Programming languages (2)
Github contributions (5)
ThinkR-open/wedding
Apr 2021 - Mar 2022
Shiny app with custom css to prepare and manage a wedding
Contributions:23 commits, 26 PRs, 39 pushes in 11 months
shiny-appcssshinycustom-cssprepare
MargotBr/agreeclust
Nov 2017 - Jan 2021
Agreement-based unsupervised clustering of a set of ratings through a latent class regression modeling framework
Contributions:105 commits, 22 PRs, 88 pushes in 3 years 3 months
regressionunsupervisedagreementmachine-learningregression-modeling
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