E T Consultant

Job #:
req36688

Organization:
World Bank

Sector:
Economics

Grade:
EC2

Term Duration:
1 year 0 months

Recruitment Type:
Local Recruitment

Location:
Washington, DC,United States

Required Language(s):
English

Preferred Language(s):

Closing Date:
6/3/2026 (MM/DD/YYYY) at 11:59pm UTC

Description

Within this architecture, the Prosperity Vertical focuses on the policies and institutions that underpin inclusive and sustainable growth, bringing together fiscal policy, public finance management, macroeconomic and poverty analysis, and private sector-enabling reforms. Prosperity's Fiscal Policy and Growth department includes the Distributional Impact of Policies Global unit (also known as Poverty). The Poverty team focuses on integrating distributional analysis of reforms and investments into operational knowledge and lending. The Poverty team comprises applied microeconomists, statisticians, data scientists, and social and behavioral scientists who support WBG teams and governments with tools like fiscal incidence analysis and fiscal microsimulation-ensuring policies and programs reduce poverty and inequality and informing lending and prior actions where relevant.

Well-designed policy reforms can lead to improvements in economic growth and sustainability, and reductions in poverty. However, part of ensuring that policies are well designed requires considering the potential winners and losers and ensuring that the most vulnerable are protected from potential short-term losses. With a tighter fiscal envelope and poverty rates that have failed to decline, policies in developing countries will have to be carefully calibrated to sustain social progress. Is there room to tighten policies without having a detrimental impact on the poor? Is there scope to better articulate social protection and to introduce more efficient, effective, and counter-cyclical risk-sharing plans? How much scope is there to use tax policy to pursue redistribution and risk-sharing objectives? What is the evidence on the likely distributional impact of each of the main fiscal policies such as direct and indirect taxes, transfers and subsidies? Answers to these questions could help countries to weather the economic slowdown and to provide a sound basis for redistributive and risk-sharing policies that are more responsive to risk and that support inclusive growth.

The Micro Modeling Lab

Embedded in the Distributional Impact of Policies Global unit, the Micro Modeling Lab (MML) is a team of data scientists and economists tasked with providing just-in-time assistance to regional teams working on the distributional impact of policy reforms. The objective is to inform the Bank's analytical and operational work, ensuring that intervention design and implementation appropriately considers the poverty and distributional impacts by providing just-in-time expertise. The Micro Modeling Lab works with Poverty economists on the ground and with other Global Solutions Groups to develop and scale tools and solutions across teams, including through testing and adaptation, development of platforms, and hands-on support to country teams. In addition, the team is tasked with capturing, curating, and disseminating operational solutions.

Scope of Work and Tasks

The Micro Modeling Lab is looking for an experienced economist or data scientist with a demonstrated track record in quantitative methods and advanced programming, including hands-on expertise in micro-econometric analysis and statistical techniques applied to policy-relevant research. The consultant will be expected to independently lead the estimation of distributional impacts of policies and alternative reforms across multiple country case studies, exercising sound judgment in methodological choices. The consultant will collaborate closely with the Poverty team to enhance, adapt, and scale existing approaches, applying best practices in programming, tool development, and reproducible research workflows. The consultant will undertake the following tasks:
• Lead fiscal incidence analyses for different country teams, ensuring methodological rigor and compliance with standards and protocols defined by the Micro Modeling Lab. All coding protocols and data archiving should be shared through GitHub and SharePoint.
• Drive the integration of fiscal incidence analyses into a global microsimulation model for cross-country comparisons, taking ownership of key components and resolving technical challenges as they arise in close coordination with the broader team.
• Lead microsimulations of alternative reform scenarios and independently produce write-ups - including assumptions, methodological choices, and findings - communicating distributional impacts of reforms clearly to both technical and non-technical audiences.
• Make substantive contributions to the development, refinement, and improvement of standardized analytical, microsimulation, and visualization tools that support the Bank's analytical and operational work, drawing on demonstrated expertise to improve robustness and scalability.
• Actively engage and share knowledge with other World Bank teams working on related issues across sectors and Global Solution Groups, contributing to cross-practice learning on microsimulation approaches.

Like all members of the Poverty Global Practice, the consultant will also be expected to contribute to the global knowledge base of the department.

Duration and location

This contract will be for one year, based in Washington, DC, with possibility of extensions contingent on performance and business need.

Selection Criteria
• Master's degree (PhD preferred) or equivalent in Economics, Statistics, or a related field.
• A minimum of 5 years of relevant professional experience applying economic data, analytical tools, and models to conduct fiscal incidence analyses, with a demonstrated track record of producing high-quality results independently.
• Proven experience building and working with microsimulation models to assess the distributional impact of alternative policy reforms. Experience working with both household and administrative data is desirable.
• Sound expertise in data analysis and programming in STATA; proficiency in R and/or Python is considered a plus. Experience using Git or other code-sharing platforms for collaborative and reproducible workflows is desirable.
• Demonstrated ability to work independently on complex analytical tasks, paired with strong collaborative skills within multicultural and multidisciplinary teams.
• Excellent written, communication, and presentation skills in English, including the ability to convey complex analytical findings clearly to both technical and non-technical audiences.
• Experience working effectively with cross-functional teams.

Note: Thisinternal requisition is open to WBG and IMF staff only (including short-termand extended term consultants/ temporaries). External candidates are requestednot to apply. In case an external candidate applies, their application will notbe considered.