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Hi! I’m Mathias Villerabel, an AI Engineer and Data Scientist passionate about leveraging data to solve real-world problems. I specialize in building scalable ML models, data pipelines, and deriving actionable insights from complex datasets. You can check my website : _Website not available. Sign in: https://www.twine.net/signup_…

Mathias Villerabel

Data Scientist, AI Engineer, Full Stack Developer, +2

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Hi! I’m Mathias Villerabel, an AI Engineer and Data Scientist passionate about leveraging data to solve real-world problems. I specialize in building scalable ML models, data pipelines, and deriving actionable insights from complex datasets. You can check my website : _Website not available. Sign in: https://www.twine.net/signup_…

Available to hire

Hi! I’m Mathias Villerabel, an AI Engineer and Data Scientist passionate about leveraging data to solve real-world problems. I specialize in building scalable ML models, data pipelines, and deriving actionable insights from complex datasets.

You can check my website : Website not available. Sign in: https://www.twine.net/signup

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Language

French

Fluent

English

Fluent

Work Experience

Data Scientist at Swiss Re

September 1, 2023 - Present

Built an IFRS 17 actuarial/financial simulation engine (cash flows, discounting, Contractual Service Margin) to benchmark EY outputs and ensure regulatory compliance. Automated end-to-end reconciliation (GL ↔ actuarial models), cutting manual work from multi-day reviews to < 2h/run and improving auditability & reproducibility. Designed and optimized PySpark pipelines in Palantir Foundry, scaling to 109+ accounting records per batch and integrating with downstream financial reporting systems.

Data Scientist at Pernod Ricard

August 1, 2023 - October 21, 2025

Developed time-series forecasting and ML models (ARIMA, gradient boosting) and designed a custom PyTorch framework for scalable training / inference. Improved 3-month demand forecasts by 12% vs. FA baseline.

Research & Applied Scientist at Synspective

January 1, 2023 - October 21, 2025

Automated detection of new construction from SAR time series (InSAR coherence + intensity). Delivered a cloud-based Earth observation platform with dynamic caching on Google Cloud, reducing data latency for SDG indicators in economics and environment. Built scalable object detection models for maritime trade (containers, cars, trucks, ships); awarded 2nd Prize at the NEDO Challenge. Applied Earth observation and machine learning methods during NASA, ESA & JAXA hackathons to address real-world challenges such as wildfire monitoring and prediction.

Machine Learning Intern at National Institute of Informatics

August 1, 2019 - October 21, 2025

Developed action detection models combining MobileNetV2 with segmentation/regression maps and LSTM for temporal recognition. Integrated deep learning into UAV systems for search & rescue and surveillance; published in IEEE Access.