E T Consultant

Overview

The World Bank is seeking an Economist or Data Scientist to estimate the distributional impacts of macroeconomic shocks, structural changes, and policy reforms across multiple country case studies. The consultant will work closely with the Poverty team to enhance, adapt, and scale existing approaches.

Key Responsibilities

• Undertake the application of macro-micro simulation models for different country teams, ensuring methodological rigor and compliance with standards and protocols defined by the MML. All coding protocols and data archiving should be shared through GitHub and SharePoint.
• Collaborate on efforts to create standardized macro-micro simulation models to strengthen just-in-time analytics, helping to resolve technical challenges as they arise in close coordination with the broader team.
• Contribute to the development, refinement, and improvement of standardized analytical, microsimulation, and visualization tools that support analytical and operational work.
• Participate in activities and exchange information with other World Bank teams working on related issues across sectors and Global Solution Groups.
• Contribute to the global knowledge base of the department.

Required Experience

A minimum of 3 years of relevant professional experience applying quantitative methods and analytical tools to poverty and distributional analysis. Experience working with both household and administrative data is desirable. Experience with micro simulation methods to assess distributional impacts is desirable. Strong experience 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 the ability to collaborate with others within multicultural and multidisciplinary teams. Experience working effectively with cross-functional teams.

Qualifications

Master's degree or equivalent in Economics, Statistics, or a related field.

Other Details