Fields | Description |
---|---|
Position | Junior Data Scientist (GIS) |
Organisation | United Nations World Food Programme (WFP) |
Country | Italy |
City | Rome |
No of Vacancies | 01 |
Project Name | N/A |
Skills and Qualifications | University degree in mathematics, data science, statistics, earth sciences, or another quantitative degree |
Experience | • Knowledge of Earth Observation data, in particular MODIS, Landsat, Sentinel-2 and Sentinel-1, and processing using python, open source or off-the-shelf software tools. • GIS skills and/or experience (QGIS, GDAL, ArcGIS Pro, Google Earth Engine) • Experience with machine learning algorithms and tools (e.g.,pyTorch, TensorFlow), artificial intelligence, deep learning and predictive analytics. • Experience using data engineering best practices (e.g. CI/CD, testing, git) • Experience working with cloud technologies or distributed computing platforms such as AWS, Azure, Google Cloud, etc. |
Salary | As per industry standards |
The consultant will join the ClEO Unit of the Research, Assessment and Monitoring Division at WFP HQ and work under the supervision of the Data Science Lead in coordination with the Data Engineering team, being responsible for:
• Data Science: The consultant will leverage statistical, geo-statistical and machine learning techniques to contribute to the analysis of complex climate, environmental and socio-economic data in support of the Unit’s products and services. These could involve, for example:
• Advanced EO time series processing such as filtering, decomposition, lag-correlation analysis, and forecasting.
• Methodologies for multi-resolution data fusion (e.g. Landsat / MODIS) and the blending of ground-truth data with remote-sensed signals.
• Analysis of dynamic land cover change patterns relevant for hazard mapping and environmental resource analysis using either classic or machine learning algorithms.
• Coordinating with other team members to transition their work from development to production on cloud-based infrastructure where/if relevant.
• Teamwork: The Consultant will be a committed and collaborative team member to support knowledge sharing and common practices within the Data Science function. They will also engage in cross-functional relationships with stakeholders in the rest of the Unit to co-design impactful analytical solutions
• Communication: The Consultant will be responsible for quality code and documentation of their work and will present their results to stakeholders as needed.
Visualizing Urban and Architecture Diagrams
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