Internship of WRI Program

Statement of Work

Background 

The Asia Foundation (TAF) is a nonprofit international development organization working to improve lives, expand opportunities, and help societies flourish across Asia. With over 70 years of experience, TAF collaborates with public and private partners to strengthen institutions, promote leadership, and conduct policy research.

With support from the DBS Foundation, The Asia Foundation in Indonesia is implementing the Accelerating Financial Inclusion for Marginalized Women in Indonesia (SHE CAN) program, starting in November 2024. The program targets 80,000 marginalized women in West Kalimantan, including women-headed households, Micro, Small, and Medium Enterprise (MSME) owners, smallholder farmers, plantation workers, low-income women, and young mothers to improve their financial literacy, increase access to inclusive financial services, and enhance overall financial resilience.

To reach marginalized women across West Kalimantan, the program adopts a low-barrier training approach designed to fit participants’ realities and remove common obstacles to participation. This includes bringing sessions closer to where women live and work, using simple and practical financial materials, and offering flexible scheduling. The same principle extends to how the program collects information: because delivery spans many locations, training cycles, and channels, data is gathered through multiple light-touch points such as participant registration, attendance, assessments, and field monitoring. The program is committed to keeping this process simple for participants while ensuring the resulting data remains accurate, well-managed, and protected.

Objective 

Delivered at scale across West Kalimantan through multiple training cycles and channels, the SHE CAN program generates a large and varied volume of data from participant registration, attendance, assessments, and field monitoring. Structured data management is therefore essential to clean, consolidate, and process this data so that it is reliable, analysis-ready, and usable for program learning and reporting.

To support this effort, the intern will work with the SHE CAN Monitoring, Evaluation, and Learning (MEL) team to clean, process, and organize training and program data so that it is accurate, well-structured, and analysis-ready. The intern will assist in performing routine data cleaning and validation using tools such as Excel, Power Pivot, and Python, conducting basic data analysis,  documenting data processing steps, and helping produce simple summaries, tables, and visualizations to support program learning and donor reporting. The role is intended to provide practical, hands-on experience in data management and analysis within an active development program.

Detailed Tasks 

The intern will work closely with the SHE CAN MEL team and implementing partners during data collection and processing to:

• Clean, validate, and standardize raw training and program datasets, including handling missing values, duplicates, inconsistent entries, and formatting issues.
• Organize and structure datasets so they are analysis-ready, consistently labeled, and well-documented.
• Support basic data processing and exploratory analysis using Excel, Power Pivot, and Python, including generating descriptive statistics, cross-tabulations, and simple summaries.
• Help prepare tables, charts, and basic visualizations that present analysis results and communicate training and program findings clearly.
• Maintain clear documentation of data cleaning steps, codebooks, and data dictionaries to ensure reproducibility and transparency.
• Support data quality checks and flag anomalies or inconsistencies to the MEL team for follow-up.
• Participate in regular team coordination meetings and assist with other MEL and data-related tasks as needed.
• Communicate and coordinate with SHE CAN local partners on data collection, data entry, and clarification of data-related queries to ensure completeness, accuracy, and timely submission of datasets.

Qualifications 

• Final-year student nearing completion, or a recent graduate, in a relevant field such as statistics, data science, economics, social sciences, public health, or a related discipline.
• Basic to intermediate skills in data cleaning, processing, and analysis using Excel and Python (e.g., pandas, NumPy), with a good understanding of datasets and data structures.
• Strong attention to detail, good organizational skills, and the ability to document work clearly and accurately.
• Interest in monitoring, evaluation, and learning (MEL), women’s empowerment, or international development, and a willingness to learn.

Application Process: Prospective interns will submit their resumes or CV, cover letters, and relevant work samples (if applicable) to id.hr@asiafoundation.org. by July 17, 2026, 05.00 PM Jakarta time. Please write “WRI  Intern: [Your name]” in the subject of the e-mail.