How to apply for Research Fellow, J-PAL South Asia

About Poverty Action Lab (J-PAL)

J-PAL is a global network of researchers who run randomized field evaluations to find out what actually reduces poverty. The South Asia office works directly with governments and implementing organizations in India, so research findings can feed into policy and programs at scale. This is a place to work if you want your analysis to be used, not just published.

About the role

This is a senior technical role leading randomized evaluations and implementation science research on education delivery at scale in India. You will run research workstreams from design through analysis and dissemination, including embedded A/B tests with government and implementing partners. You also mentor Research Associates and manage work allocation across multiple projects. The work feeds into policy briefs, academic papers, and practical tools for policymakers and practitioners.

A typical day

A typical day might involve reviewing a research protocol or survey instrument, meeting with Research Associates and field teams on data quality, and running or checking quantitative analysis in Stata, R, or Python. You may also coordinate with government or implementing partners on an embedded A/B test, and draft or review sections of a policy brief or academic paper. Travel within India is part of the role, so some days will be spent with partners or field teams rather than at a desk.

Who Poverty Action Lab (J-PAL) is looking for

• Master's degree in economics, public policy, development, or a related field, with at least 5 years of applied research experience running randomized evaluations.
• Proficient in Stata, R, or Python, and able to oversee quantitative analysis done by others.
• Has built research protocols, survey instruments, and data systems, and has coordinated with field teams and implementing partners.
• Willing to travel within India and occasionally internationally, and able to commit to more than two years starting 3–10 August 2026.

Tips for this application

• Name specific randomized evaluations you have led or co-led, including the sector, sample size, and your exact role in design, measurement, and analysis.
• Show experience with embedded A/B tests or implementation science, not just stand-alone RCTs, since this role involves testing within delivery at scale.
• List your software proficiency with concrete examples: which datasets you cleaned, which code you wrote, which analysis you oversaw in Stata, R, or Python.
• State your availability for the 3–10 August 2026 start and confirm you can commit for more than two years.
• Mention any experience working with Indian government agencies or implementing organizations, since the role is built on those partnerships.

What to cover in your cover letter

Explain why you want to work on education delivery at scale in India, and connect that to J-PAL's approach of generating evidence through randomized evaluations. Describe one or two evaluations you led, including your role in protocol design, survey instruments, data systems, and analysis. Show you can mentor Research Associates and manage work across multiple projects. Confirm your start-date availability and your commitment beyond two years.

Research before applying

• Read J-PAL South Asia's published evaluations and policy briefs on education, especially any work on delivery at scale in India.
• Look at how J-PAL describes its partnerships with Indian government and implementing organizations, and what those partnerships require in practice.
• Check J-PAL's evaluation methods and their approach to embedded A/B tests and implementation science.
• Find out who leads the education sector work at J-PAL South Asia and what projects are currently active.

Likely interview topics

Based on the job description, expect questions about:

• How you would design a randomized evaluation or embedded A/B test for an education delivery program at scale in India.
• Your experience developing research protocols, survey instruments, and data systems, and how you ensured data quality with field teams.
• A time you managed multiple research projects and allocated work across Research Associates.
• How you have translated research findings into policy briefs, academic papers, or tools for policymakers and practitioners.
• Your technical approach in Stata, R, or Python, including how you oversee quantitative analysis done by others.

Common mistakes to avoid

• Describing randomized evaluations in general terms without naming the specific studies you designed, measured, or analyzed.
• Claiming software proficiency without showing which datasets, code, or analyses you actually handled in Stata, R, or Python.
• Ignoring the start date and commitment requirement, or applying without confirming you can begin 3–10 August 2026 and stay more than two years.