Support for Development of Social vulnerability, Risk vulnerability and Poverty metrics for Sub-Saharan countries (GIS)
Support the development of metrics for social vulnerability and poverty research
This opening expired 5 years ago.
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Overview
Support the development of metrics for social vulnerability and poverty research
You have:
- Bachelor's (or higher) in Computer Science, Geomatics, Geography, Statistics, or related field with strong interest in Data Science
- Practical experience in data preprocessing and data collection techniques
- Understanding of analytical techniques such as predictive analytics, event detection/prediction, and data visualization
- Experience in machine learning modeling is a plus
- Applied knowledge of programming languages such as Python or R
- Experience in working with geodata
Contract
This is a UNV contract. More about UNV contracts.
The online volunteers will participate in developing models to derive a) Disaster risk, poverty risk and so-called social vulnerability metrics for development research and the Sustainable Development Goals (SDGs). The online volunteers will work under SDG AI Lab supervision. The main tasks will be: 1) Build upon the existing methodology(ies) provided by the Lab and support the team in the data collection process as well as the semantic / logical development of the process. 2) Work with geographical datasets and data preprocessing, such as raster files or vector shapefiles, xarray datasets, netcdf files and geo - tagged csv tabular data or similar. 3) The project is aiming to deploy at least one model which incorporates information of an existing survey dataset with derived and collected datasets by the online volunteers. SDG AI Lab will support the online volunteer as needed, with bi-weekly check-ins and maintain a regular communication through MS Teams and GitHub + Jira.
- Technology development
Database design, administration and maintenance
IICPSD’s SDG AI Lab initiative (sdgailab.org) requires assistance in developing and implementing metrics for social vulnerability, risk vulnerability and poverty using geospatial data and machine learning techniques. The project envisions experimentation with geospatial technology and data exploration, statistical models and ML -based solutions for the metrics development. The Lab provides in-house expertise, resources, and research support to various UNDP projects to mainstream digital transformation to development problems and to contribute to the achievement of the Sustainable Development Goals.
Volunteers: 5 needed
11-20 hours per week / 13 weeks
Bachelor’s (or higher) in Computer Science, Geomatics, Geography, Statistics, or related field with strong interest in Data Science; Practical experience in data preprocessing, data collection techniques; Understanding and knowledge of analytical techniques such as predictive analytics, event detection / prediction, data visualization, and experience machine learning modeling is a plus; Applied knowledge of programming languages, such as Python or R; Experience in working with geodata.
Global
- English
Potential interview questions
| Can you describe a data project you've worked on and your role in it? | The interviewer wants to assess your practical experience and contribution to previous data projects. | Outline the project's objectives, your specific tasks, and the outcomes, emphasizing your skills. |
| How do you approach working with various types of datasets? | The interviewer is interested in your data handling and preprocessing techniques. | Pro members can see the explanation. |
| What experience do you have with geospatial data analysis? | Pro members can see the explanation. | Pro members can see the explanation. |
Added 5 years ago
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Updated 1 year ago
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Source:
onlinevolunteering.org
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