Mathias Villerabel, Data scientist

Description

Data scientist and research engineer with 6+ years across consumer goods, geospatial analytics, and finance. I build reliable ML models and large-scale data pipelines and translate business needs into production systems. Comfortable in multicultural teams (FR/CH/JP

Industry field of expertise

Languages

French
Native or bilingual
English
Native or bilingual

Workplace preferences

Can work on-site

Paris (up to 50km)

SwissRe
Data Scientist
BANKING AND INSURANCE
September 2023 - May 2025 (1 year and 8 months)
Zurich, Switzerland
Built IFRS 17 actuarial/financial simulation engine (cash-flows, discounting, contractual service margin) to benchmark EY consulting outputs and ensure regulatory compliance.
Automated end-to-end reconciliation (GL ↔ actuarial models), reducing manual work from multi-day reviews to <2 h/run and improving auditability & reproducibility.
Designed and optimized PySpark pipelines in Palantir Foundry, scaling to 10⁹+ records/batch and integrating with downstream financial reporting systems.
Python Palantir Foundry PySpark CI/CD Cloud computing
Pernod Ricard
Data Scientist
WINE AND SPIRITS
January 2023 - August 2023 (7 months)
Paris, France
Built time-series forecasting and ML models (ARIMA, gradient boosting) and designed a custom PyTorch framework for scalable training/inference, improving 3-month demand forecasts by 12% vs. FA baseline.
Python Machine learning Forecast Pytorch MLflow
Synspective
Applied Scientist
AVIATION AND AEROSPACE
December 2019 - January 2023 (3 years and 1 month)
Tokyo, Japan
Automated detection of new construction from SAR time series (InSAR coherence + intensity), improving urban growth monitoring.
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, monitoring container, car, truck, and ship flows; 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.
Python Data science satellite Google cloud Deep Learning

Check out Mathias's experience

A

Agatha Frydrych

Backend Java Software Engineer

4.7

(3)

2

B

Baptiste Duhen

Fullstack developer

4.6

(4)

5

A

Amed Hamou

Senior Lead Developer

4

(2)

7

A

Audrey Champion

Web developer

4.3

(3)

4

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M.Sc. Computer Science
Sorbonne University France
2019
Machine learning, agents, robotics, operational research, decision
B.Sc. Computer Science & Mathematics
Sorbonne University
2016
Algorithmic, Statistics, Software Engineering, Network, Linux

Data Scientist