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I'm Adrien Morel, a Data Scientist who designs reliable ML systems from data pipelines to evaluation, APIs, and monitoring. I enjoy turning complex data into actionable insights with rigorous experiments and robust production-ready tooling. I'm currently working on Vélib’ Forecast Paris as an independent ML Engineer, building end-to-end forecasting pipelines and serverless deployments on Google Cloud Platform. Previously I automated railway track anomaly detection at SNCF Réseau and analyzed customer feedback and mobility data at Transdev, always focusing on data quality, interpretability, and maintainability.…I'm Adrien Morel, a Data Scientist who designs reliable ML systems from data pipelines to evaluation, APIs, and monitoring. I enjoy turning complex data into actionable insights with rigorous experiments and robust production-ready tooling. I'm currently working on Vélib’ Forecast Paris as an independent ML Engineer, building end-to-end forecasting pipelines and serverless deployments on Google Cloud Platform. Previously I automated railway track anomaly detection at SNCF Réseau and analyzed customer feedback and mobility data at Transdev, always focusing on data quality, interpretability, and maintainability.

Adrien Morel

Data Scientist, AI Engineer, AI Developer, +4

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I'm Adrien Morel, a Data Scientist who designs reliable ML systems from data pipelines to evaluation, APIs, and monitoring. I enjoy turning complex data into actionable insights with rigorous experiments and robust production-ready tooling. I'm currently working on Vélib’ Forecast Paris as an independent ML Engineer, building end-to-end forecasting pipelines and serverless deployments on Google Cloud Platform. Previously I automated railway track anomaly detection at SNCF Réseau and analyzed customer feedback and mobility data at Transdev, always focusing on data quality, interpretability, and maintainability.…I'm Adrien Morel, a Data Scientist who designs reliable ML systems from data pipelines to evaluation, APIs, and monitoring. I enjoy turning complex data into actionable insights with rigorous experiments and robust production-ready tooling. I'm currently working on Vélib’ Forecast Paris as an independent ML Engineer, building end-to-end forecasting pipelines and serverless deployments on Google Cloud Platform. Previously I automated railway track anomaly detection at SNCF Réseau and analyzed customer feedback and mobility data at Transdev, always focusing on data quality, interpretability, and maintainability.

Available to hire

I’m Adrien Morel, a Data Scientist who designs reliable ML systems from data pipelines to evaluation, APIs, and monitoring. I enjoy turning complex data into actionable insights with rigorous experiments and robust production-ready tooling.

I’m currently working on Vélib’ Forecast Paris as an independent ML Engineer, building end-to-end forecasting pipelines and serverless deployments on Google Cloud Platform. Previously I automated railway track anomaly detection at SNCF Réseau and analyzed customer feedback and mobility data at Transdev, always focusing on data quality, interpretability, and maintainability.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Language

French

Fluent

English

Advanced

Italian

Fluent

Spanish; Castilian

Intermediate

Work Experience

ML Engineer at Vélib’ Forecast Paris

September 1, 2024 - Present

Designed and deployed an end-to-end ML system to forecast bike availability across a large urban network. Built reproducible data ingestion, feature engineering, model training and batch inference pipelines. Implemented model evaluation and monitoring (data quality, drift, performance) over 1,500+ stations with automated reporting. Deployed serverless infrastructure on GCP (Cloud Run, Cloud Storage, Scheduler) and exposed predictions via a FastAPI API.

Data Scientist at SNCF Réseau

October 1, 2022 - May 1, 2023

Automated detection of geometric anomalies across 400 km of railway tracks using statistical and signal-based methods. Designed interpretable indicators to improve the reliability of field diagnostics. Built visualization tools to support maintenance engineers in decision-making. Result: Reduced manual analysis time by 50% for a team of 12 agents.

Data Scientist / VBA Developer at Transdev

June 1, 2021 - September 1, 2022

Built an NLP pipeline to analyze customer feedback (scraping, preprocessing, sentiment analysis). Designed dashboards to monitor fuel efficiency and operational KPIs. Standardized multi-source data pipelines and automated reporting workflows. Migrated historical datasets to Snowflake for scalable analytics.