WBG Pioneer - LSMS Survey Innovation Fellow
Contribute to AI-focused survey innovation for the World Bank.
Overview
Contribute to AI-focused survey innovation for the World Bank.
You have:
- Currently enrolled in an undergraduate program in economics, statistics, data science, computer science, or a related field.
- Demonstrated interest in household surveys, development research, data quality, AI, natural language processing, or related methodological topics.
- Strong analytical, quantitative, research, and problem-solving skills, with attention to detail and willingness to learn new tools.
- Basic familiarity with data analysis, statistical software, or programming languages such as Python, R, or Stata; strong written and verbal communication skills in English.
ul { list-style-type: disc; list-style-position: outside; padding: 0 0 0 20PX; } li { float: none; } WBG Pioneer - LSMS Survey Innovation Fellow
Job #: req37634 Organization: World Bank Grade: T3 (no-fee) Location: Washington, DC,United States Hiring Manager:Amparo Palacios-Lopez Required Language(s): English Preferred Language(s): Closing Date: 8/12/2026 (11:59pm UTC) Description
WBG Pioneers, the World Bank Group’s Internship Program, offers undergraduate and postgraduate students a high impact learning experience at the heart of global development. Participants gain hands on experience in a diverse and dynamic environment, contribute fresh perspectives and innovative ideas, and connect with international professionals working to end poverty on a livable planet.
The Development Economics Survey Unit (DECSU), in the World Bank Group’s Development Economics Vice Presidency, supports the production and use of high-quality household survey data in low- and middle-income countries through the Living Standards Measurement Study (LSMS). LSMS works with national statistical offices and other partners to design, implement, and analyze multi-topic household surveys that inform policy and research on poverty, livelihoods, agriculture, labor, welfare, and related development outcomes.
DECSU is developing an AI-focused work program to improve survey implementation and data quality through recent advances in large language models and generative AI. This work includes using interview audio to create analyzable text through recording, transcription, translation, and integration with survey metadata; strengthening survey quality control and error detection; and exploring how open-ended responses can support simpler, more respondent-centric questionnaire design.
Duties and Responsibilities
The Fellow will contribute to the design and development of an end-to-end pipeline to capture high-quality audio from field survey interviews, transcribe and translate audio across languages, including low-resource languages such as Nepali, Bengali, and Swahili, and integrate the resulting text with survey metadata for quality control and analysis. The assignment will provide practical exposure to survey methodology, data quality monitoring, field experiment implementation, and applied research using LLMs and generative AI.
The scope of work will include reviewing and synthesizing the landscape of available automatic speech recognition (ASR) and translation technologies relevant to low-resource languages used in survey contexts; supporting the testing and evaluation of transcription and translation model outputs, including the design and application of accuracy benchmarks; contributing to data preparation, cleaning, and structuring tasks that enable the integration of audio-derived text with structured survey metadata; and assisting in the documentation of pipeline components, field protocols, and evaluation results to support the broader research and development effort. In consultation with the research team, the Fellow may also contribute to research outputs and develop an independent research question using project data.
Selection Criteria
- Currently enrolled in an undergraduate program in economics, statistics, data science, computer science, or a related field. - Demonstrated interest in household surveys, development research, data quality, AI, natural language processing, or related methodological topics. - Strong analytical, quantitative, research, and problem-solving skills, with attention to detail and willingness to learn new tools. - Basic familiarity with data analysis, statistical software, or programming languages such as Python, R, or Stata; strong written and verbal communication skills in English.
No-Fee Internship Eligibility
This position is offered under the WBG Pioneers No-Fee Internship Track. Students may be offered a no-fee STT appointment provided that they either: (a) are enrolled in a Master's, PhD, or similar graduate program during the entire internship (or are in the fifth year or higher of a degree program in countries where higher education is not divided into undergraduate and graduate stages) and provide an official letter from their university confirming that the internship fulfills academic requirements for at least one term of study; or (b) are enrolled in undergraduate or graduate studies and receive a stipend from their university at least equivalent to the minimum STT T1 fee level in effect at the start of the assignment, as confirmed by an official university letter.
Note: Please limit your applications to a maximum of three positions. Applications exceeding this limit will not be considered.
WBG Culture Attributes: 1. Sense of urgency: Anticipate and quickly respond to the needs of internal and external stakeholders. 2. Thoughtful risk-taking: Challenge the status quo and push boundaries to achieve greater impact. 3. Empowerment and accountability: Empower yourself and others to act and hold each other accountable for results.
The World Bank Group values diversity and encourages all qualified candidates who are nationals of World Bank Group member countries to apply, regardless of gender, gender identity, religion, race, ethnicity, sexual orientation, or disability. Sub-Saharan African nationals, Caribbean nationals, and female candidates are strongly encouraged to apply.
Potential interview questions
| Describe a time when you used data analysis in a project. | To assess your ability to apply data analysis skills in real-world situations. | Provide a specific example detailing your role, the data involved, and the impact of your analysis. |
| What motivates your interest in household surveys? | To understand your passion and commitment to the field. | Pro members can see the explanation. |
| Explain how you approach problem-solving when faced with data discrepancies. | Pro members can see the explanation. | Pro members can see the explanation. |
| Have you ever had to learn a new programming language or software quickly? How did you manage? | Pro members can see the explanation. | Pro members can see the explanation. |
| Can you provide an example of how you've worked with a team on a project? | Pro members can see the explanation. | Pro members can see the explanation. |
| What challenges do you foresee in applying AI technologies to household surveys? | Pro members can see the explanation. | Pro members can see the explanation. |
| How do you ensure quality in your research work? | Pro members can see the explanation. | Pro members can see the explanation. |
| What are your future career goals in development economics? | Pro members can see the explanation. | Pro members can see the explanation. |
Added 3 days ago
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Updated 2 hours ago
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Source:
worldbank.org
