Remi Turpaud
Data Architect
France
Summary
👤
Senior🎓
Top SchoolRemi Turpaud is a Data Architect with nine years of experience helping large enterprises solve complex analytics problems at scale, currently leading analytic architecture and ecosystem practice for Teradata across South East Asia, Korea, Australia and New Zealand. He has a strong track record delivering end-to-end data warehouse, BI and analytics platforms across industries—telecom, finance, transport, energy and utilities—and has driven performance tuning and global implementations that materially improved runtime and resource consumption. Hands-on in both pre-sales and delivery, he blends platform design (Teradata, Cloudera/Hortonworks) with data science enablement and has led teams and offshore delivery centers. An active technologist and open source contributor, he contributed ML-focused improvements to GoogleCloudPlatform cloudml samples, showing practical ML engineering experience beyond pure architecture. Based in France with a master’s in computer science and electronics from ESIEA, he pairs deep technical experience with customer-facing strategy to turn complex requirements into operational analytics platforms. Colleagues would describe him as a pragmatic architect who moves quickly from PoC to production while coaching teams to adopt scalable patterns.
9 years of coding experience
11 years of employment as a software developer
Master, Computer sciences, electronics, automated systems, Master, Computer sciences, electronics, automated systems at ESIEA - École d'Ingénieur·e·s d'un numérique utile
French, English, Spanish
Github Skills (7)
pandas10
keras10
machine-learning10
tensorflow10
python10
data-processing9
gcp8
Programming languages (4)
Github contributions (5)
GoogleCloudPlatform/cloudml-samples
Dec 2017 - Feb 2018
Cloud ML Engine repo. Please visit the new Vertex AI samples repo at https://github.com/GoogleCloudPlatform/vertex-ai-samples
Role in this project:
ML Engineer
ML EngineerContributions:11 commits, 3 PRs, 12 comments in 1 month
Contributions summary:Remi primarily contributed to the Keras model within the census example. Their work included improving the `generator_input` function for data processing, adding minibatch functionality, and updating the activation function. The user also modified the optimizer to RMSprop, and made adjustments for Python 3 compatibility. Further changes show cleanup and small style improvements.
gcpcloudml-samplescloudmldeep-learninggooglecloudplatform
RemiTurpaud/superset-td
Aug 2017 - Sep 2017
Contributions:15 commits, 14 pushes, 1 branch in 16 days
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