WBG Young Professional

The World Bank Group’s Young Professionals Program (YPP) offers exceptional professionals the opportunity to apply their specialized technical expertise, broaden their experience, and contribute to solutions to pressing development challenges. YPs work across the World Bank Group in support of the mission to create a world free of poverty on a livable planet, completing rotations to deepen technical and operational knowledge and develop as future leaders in global development.

Responsibilities

• Design and implement applied research embedded in World Bank operations, using randomized and quasi-experimental methods to determine what works, for whom, and under what conditions.
• Develop, test, deploy, and maintain data and AI applications tailored to development contexts, moving solutions from prototype to operational use by World Bank teams and government counterparts.
• Support LEADS engagements, including portfolio design workshops, learning agendas, rapid experiments, A/B tests, and evidence-based adaptation of projects and programs.
• Assess whether evidence-backed solutions are ready to scale, require further adaptation and testing, or are not suitable for replication in a specific context.
• Build predictive and analytical models that inform targeting, implementation, replication, adaptation, and scaling decisions.
• Work with administrative, survey, geospatial, satellite, text, audio, and other non-traditional data, including data generated under real-world operational constraints.
• Contribute to DECDI's institutional platforms and global public goods, including LEADS, ImpactAI, and MEGA, to make evidence and analytics accessible within World Bank workflows.
• Apply responsible AI and sound data governance practices, including privacy and data protection, bias and robustness testing, model evaluation, reproducibility, and clear documentation of limitations.
• Produce decision-oriented outputs, including analytical products, academic papers, policy briefs, presentations, technical documentation, and training materials.
• Collaborate with government counterparts, operational teams, researchers, engineers, and field staff, and help build client capacity through workshops and training programs.

Requirements

• A minimum of a master’s degree in economics, public policy, computer science, data science, statistics, machine learning, engineering, quantitative social science, or a closely related field.
• 2-6 years of relevant professional experience in applied microeconomic research, impact evaluation, development policy, data science, machine learning, AI product development, or a closely related area.
• Strong quantitative and analytical skills, with demonstrated expertise in at least one of the following areas: causal inference and experimental methods; predictive modeling and machine learning; or data-intensive application development.
• Proficiency in Python, R, Stata, and/or SQL, commensurate with the candidate's technical profile, together with familiarity with reproducible workflows and version control.
• Experience working with complex real-world data, including administrative, field, survey, geospatial, satellite, text, or other non-traditional sources.
• Experience in developing-country, low-connectivity, or capacity-constrained settings is an advantage.
• Demonstrated ability to work effectively with government counterparts, operational teams, and multidisciplinary technical colleagues, adapting advice to institutional and implementation realities.
• Commitment to responsible data and AI practices, including privacy, fairness, transparency, and clear communication of methodological and model limitations.
• Demonstrated interest in international development and the World Bank Group's mission.
• Excellent written and verbal communication skills, including the ability to explain technical methods and findings to non-technical decision-makers.
• Ability to work effectively in diverse, team-based environments, manage multiple priorities under tight deadlines, and travel regularly to client countries.
• Proficiency in English; fluency in additional languages is an advantage.

Skills

• Applied Microeconomic Research
• Impact Evaluation
• Development Policy
• Data Science
• Machine Learning
• AI Product Development
• Causal Inference
• Experimental Methods
• Predictive Analysis
• Data-Intensive Application Development
• Python
• STATA
• SQL
• Reproducible workflows
• Version Control Systems
• Complex Data Analysis
• Administrative Data Analysis
• Field Data Analysis
• Survey Data Analysis
• Geospatial Analysis
• Satellite Image Analysis
• Text Data Analysis
• Responsible Data Use
• AI Ethics Frameworks
• Technical Communication

Languages

English