Data Scientist Volunteer at MapAction

General Volunteer information

Data Science Volunteer

Your ultimate goal will always be to bring greater insights to humanitarian crises, leading to better outcomes for the people affected. In practice this could be anything from identifying and preparing appropriate datasets, writing code, evaluating data quality, conducting statistical analysis, creating visualisations and data models and much more. Increasingly there are opportunities to deploy overseas, particularly in support of our growing work on anticipatory action.

Within this role you will have the opportunity to be involved in:

• Support the development and maintenance of data-science products, mainly using Python
• Perform statistical analysis of geospatial data
• Create data visualisations and dashboards, using Python (e.g. Streamlit, Dash, Voila) and/or R libraries (Shiny)
• Conduct reviews of exciting literature and data-analytics products and methods
• Support the design and management of data-science projects
• Convey analysis results clearly and in a language accessible to a non-technical audience
• Engage in conversations with partners
• Prepare and provide internal and external training on data-science products and methodologies
   

Role specific criteria

The criteria listed here are in addition to the general criteria outlined for all volunteers

Essential

• At least one year of professional experience working in the area of data science or data analytics is required
• Intermediate to advanced programming skills in Python and common data-science libraries (e.g. Geopandas, Scikit-learn, Jupyter Notebook, Streamlit, Dash)
• Experience with git and version control
• Strong data editing, analysis and processing skills
• Experience in in particular working with non-technical clients

Desirable

• Experience with Google Earth Engine and remote sensing
• Experience with Streamlit
• Experience with GIS and software development, or related subject or equivalent professional experience
• Experience with other developer tools (aws, docker, etc.)
• Experience in database interrogation and analysis tools, such as Hadoop, SQL
• Practical experience with one or more of these: GeoServer, PostgreSQL / PostGIS, OpenLayers, Leaflet, MapBox, QGIS Server, QGIS, GeoExt and/or ESRI ArcGIS Suite, MapServer, MapInfo