The Financial Inclusion Data Wrangler will support the development of MIX's financial inclusion practice, in close collaboration with the analysis and product teams. The Data Wrangler will be responsible for investigating data resources on financial inclusion, managing large datasets, as well as analyzing, mapping and visualizing data.
The Financial Inclusion Data Wrangler will work together with the MIX Financial Inclusion Team to shape and deliver MIX's data and analysis on financial inclusion. Responsibilities include the following:
- Investigating and working to collect, clean and document data on financial inclusion, including from external platforms, including data on financial service providers and contextual information on different developing countries such as population, poverty, and infrastructure.
- Conducting analysis of data on financial inclusion, including mapping and other types of data visualization, and writing reports. Mapping work will include data set geo-coding and building maps using proprietary tools for online display. Analysis of data will be based on hypotheses and questions from key stakeholder groups.
- Informing organizational strategy for data collection, aggregation, and dissemination
- Outreach to key data partners and stakeholders
- General support to MIX's analysis and research functions
Skills:
- Solid data manipulation and analysis skills, including:
- Editing and augmenting geographic files of both raster and vector formats
- Data cleaning, reformatting, and summarizing, using various software and programming languages
- Research and analytical skills that support a clear and in-depth understanding of the local financial inclusion landscape and afford decision-makers with the tools and knowledge they need to support increased financial inclusion
- Ability to learn software and design techniques quickly
- Extreme attention to detail and thorough work ethic
- Ability to communicate ideas, problems and questions succinctly to the FI team
Qualifications:
- Master's degree in a scientific discipline including Information Science, Economics, or Statistics
- Familiarity with geo-spatial software, such as QGIS and TileMill
- Basic understanding of CSS/HTML, Python, GDAL and statistical software, such as R
- Desire to learn, work with others and help advance the financial inclusion movement
