E T Consultant

At the World Bank, a member of the World Bank Group (WBG), you’ll join a diverse, global community working across cultures, disciplines, and borders to address the world’s most pressing development challenges. With 1.2 billion young people reaching working age in the decade ahead, the challenge of job creation has never been greater. Through partnerships across 145 countries and more than 182 offices worldwide, we work with governments, private sector, development partners and other stakeholders to invest in people, strengthen markets, and deliver scalable, data-driven solutions that generate more and better jobs and improve lives. For more information, visit The DIP in EAP is expanding its use of high-frequency, nontraditional data sources and AI-enabled workflows to support economic monitoring, poverty analysis, price data collection, and policy surveillance across the region. These activities require specialized expertise in machine learning, large language models (LLMs), data engineering, web data acquisition, quality assurance systems, and statistical production pipelines. Jeronimo Luza has been providing critical support in the development and operationalization of these systems, including text-processing pipelines, product classification models, source discovery workflows, data quality controls, dashboard development, and country-level implementation of real-time monitoring tools. Recent work has included the deployment and validation of large-scale classification systems, source-search automation, country testing, dashboard enhancements, and survey-to-price integration workflows. Objective The objective of the assignment is to provide specialized technical support for the design, implementation, maintenance, and scaling of data science and AI-enabled monitoring systems that generate timely indicators and analytical products to support operational and analytical work programs. Duties and Responsibilities 1. Design, develop, and maintain machine-learning and AI-based pipelines for economic and social monitoring. 2. Support large-scale classification and extraction systems for structured and unstructured data, including product, price, news, and survey datasets. 3. Develop and refine methodologies for entity classification, taxonomy mapping, semantic search, embeddings-based approaches, and LLM-assisted workflows. 4. Implement quality assurance procedures, validation protocols, and error-detection systems to improve the accuracy and reliability of analytical outputs. 5. Support the acquisition, processing, integration, and harmonization of data from web sources, administrative systems, and survey datasets. 6. Develop automated dashboards, monitoring tools, and analytical products used for operational decision-making and policy analysis. 7. Conduct country-level testing, validation, and deployment of monitoring systems and associated workflows. 8. Prepare technical documentation, methodological materials, and user guidance for developed systems. 9. Collaborate with economists, data scientists, country teams, and operational staff to translate business requirements into technical solutions. 10. Provide troubleshooting, maintenance, and continuous improvement support for production systems. Expected Deliverables

• Operational AI and data-processing pipelines supporting real-time monitoring activities.
• Enhanced classification and extraction models for economic datasets.
• Country-level implementation and validation reports.
• Data quality assessment and monitoring products.
• Automated dashboards and reporting tools.
• Technical documentation and reproducible analytical workflows.
• Support materials and analytical inputs for regional and country work programs.