Data Analyst Internship
Washington, DC /
Nithio – Risk Analytics /
Nithio is a venture-backed energy finance platform that provides services to businesses, capital providers, governments, and other stakeholders in the distributed energy sector in Africa. The company aims to address the acute need for modern energy access on the continent by providing a sustainable infrastructure for capital delivery, offering state-of-the-art underwriting tools, and a powerful information sharing platform for stakeholders to identify high-need grant recipients and credit-worthy customers. The platform offers flexible financing options by intermediating across providers of debt, concessional finance, and grants and leveraging partnerships with leading financial institutions and multilateral organizations.
The successful candidate will have a strong quantitative background, experience working with large datasets and statistical packages in R, and an entrepreneurial mindset. Preference will be given to applicants with experience in geospatial analysis, machine learning, and/or experience on the African continent.
This position will perform a range of duties including, but not limited to, the following:
- Working with the Nithio Analytics team, strategic partners (i.e. Fraym.io), and clients to clean, process, merge, and analyze a wide array of data sources including household surveys, consumer data, and payment histories to expand, deepen, and refine the Nithio underwriting tool
- Creating and maintaining documentation relating to data management and processes, including data dictionaries and methodology notes, for both internal and external use
- Supporting customized client engagements (e.g., investors, distributed energy companies, policymakers, and development agencies)
- Preparing analytical products, including presentations, briefings, and other materials
- Supporting the development of product offerings and capabilities such as machine learning applications and underwriting tools and packages.
- Currently enrolled in or recently completed a Bachelor’s or Master’s program in a related field.
- Training in statistical methods, econometrics, machine learning, and/or geospatial analysis.
- Experience with financial modeling or risk analysis is a plus.
- Intermediate statistical software skills (ideally R) and advanced skills in Microsoft Excel and PowerPoint.
- Experience cleaning, combining, and storing multiple sources of data in an organized manner.
- Strong research skills, including literature reviews.
- Eye for crafting clean, creative, and effective data visualizations.
- Outstanding communication and writing skills.
- Adaptability, confidence, and a can-do attitude.
As a lean, entrepreneurial company, flexibility and willingness to pitch in wherever needed is critical.