Earth Observation Data Scientist — Geospatial Analytics

Uni Systems; Ispra; In loco; EUR 45.000 - 65.000; Tempo pieno

Descrizione del lavoro

Uni Systems is seeking an Environmental Data Scientist for the UniQue Ispra team. The role focuses on collecting, organizing and analyzing large environmental datasets, including Earth Observation data and model outputs, using Python and R in Linux/Unix environments.

You will develop data processing workflows, build tools for data quality control, and support multidisciplinary projects by integrating heterogeneous data sources and reporting findings to stakeholders.

Competenze

• Master degree with 13+ years of relevant experience.
• Proficiency in Python and R.
• Experience in Unix environments.
• Experience managing data in formats (CSV, NetCDF, Shapefile).
• Expertise in geospatial data and Earth Observation data.
• Experience in statistical data analysis (≥2 years).
• Experience applying machine learning to environmental data.
• Strong written and verbal English skills.
• Ability to work with large, heterogeneous datasets.

Mansioni

• Gather and organize data from existing databases and sources.
• Develop tools to read data in different formats and organize into consistent datasets.
• Develop tools for data analysis, harmonization, quality control and visualization.
• Support processing and analysis of Earth Observation data.
• Assist assessment of EO data and model outputs using reference datasets.
• Help prepare and implement data processing and analysis workflows.
• Manage and analyze large datasets from diverse sources.

Conoscenze

Python

R

Unix

Geospatial data

Earth Observation

Machine learning

Environmental sciences

IDL

Formazione

Master Degree

Strumenti

IDL

Descrizione del lavoro

Uni Systems is seeking an Environmental Data Scientist for the UniQue Ispra team. The role focuses on collecting, organizing and analyzing large environmental datasets, including Earth Observation data and model outputs, using Python and R in Linux/Unix environments.

You will develop data processing workflows, build tools for data quality control, and support multidisciplinary projects by integrating heterogeneous data sources and reporting findings to stakeholders.