Analysis and Visualization of Mobility and Location Data at United Nations Development Programme (UNDP)

Task description
This assignment seeks to aggregate two-wheeler motorcycle activity and map it to the locations in Tana River County, providing valuable insights into patterns of movement of peace committees. Specifically, the volunteer will be expected to:

• Clean, anonymize and aggregate various daily and weekly Excel datasets from the 12 two-wheeler motorcycles. The datasets collected over a period of 6 months include variables such as fuel consumption, mileage, start and end locations, parking times, etc.
• Analyze the data to help us understand where users (peace committees) begin and end their journeys; produce point of interest data from frequently accessed locations; patterns and trends in fuel consumption, uncover insights how users move, etc.
• Map the transit data, GPS coordinates and route information through various maps including but not limited to mobility heat maps, flow maps, origin-destination maps, congestion maps, activity space maps, transit maps, etc. The visualizations should provide coverage of mobility activity across the county to help us understand travel patterns of the respective peace committees and how these differ over time

Requirements
Required experience

• Data analysis: The volunteer should have experience in working with large datasets, cleaning and preprocessing data, and conducting statistical analysis. They should be comfortable working with programming languages such as Python, R, SQL.
• Data visualization: The volunteer should have experience in creating effective visualizations that communicate insights from data. We are keen on having someone with either Geographic Information System (GIS) experience who is familiar with web-based mapping tools like Google Maps, Mapbox, ArcGIS Online and techniques that can be used to create a wide range of maps that incorporate location-based information or one who is familiar with data visualization libraries and tools such as matplotlib, ggplot, or Tableau.
• Domain knowledge: The volunteer should have some understanding of either transportation, urban planning, or logistics.
• Problem-solving: The volunteer should be able to think critically and creatively about how to use mobility data to solve specific problems or answer key questions. They should be comfortable working with stakeholders to identify key challenges and develop data-driven solutions.
• Communication: The volunteer should be able to communicate complex technical concepts and insights to a non-technical audience. They should be able to develop compelling visualizations that help stakeholders understand the implications of the data.