Pierre Gutierrez

I am an expert in data science and machine learning with over 12 years of experience, specializing in the analysis of physical, environmental, and industrial data.

I have held Head of Data Science positions in climate tech and medtech, where I designed and deployed complete pipelines: data acquisition, pre-processing, modeling, robust validation, and production deployment.

My areas of expertise:

- Anomaly detection (univariate, multivariate, ML, robust methods)

- Machine learning applied to geospatial and environmental data

- Remote sensing (Sentinel-1, Sentinel-2, very high-resolution data)

- Industrial time series and sensors

- Structuring data teams / ML strategy

- Model auditing and rigorous performance evaluation

Examples of recent projects:

- Prediction of soil organic carbon from satellite data

- Annual mangrove mapping (NGO)

- Biomarker prediction from NIR spectral data

- Industrial anomaly detection via deep learning

I prioritize impact-driven projects: climate, environment, industry, health — especially when it involves transforming complex scientific data into robust decision-support tools.

I can be involved:

- as a Fractional Head of Data Science

- on exploratory / POC missions

- as technical reinforcement on complex subjects

- in ML audit or structuring

My approach is pragmatic: understand the data, build solid baselines, measure correctly, then optimize.