WBG Pioneer - AI Data Scientist Intern

Every World Bank-financed project depends on systems that track how money is spent, how risk is managed, and how communities are protected. ITSFD builds those systems—this internship is a chance to work on them directly. Background/Organizational Context The World Bank Group (WBG) finances development projects across the globe through three distinct institutions, the International Bank for Reconstruction and Development and the International Development Association (IBRD/IDA), the International Finance Corporation (IFC), and the Multilateral Investment Guarantee Agency (MIGA). The Information and Technology Solutions (ITS) Vice Presidency of the World Bank Group delivers a wide portfolio of technology products and services that enable the WBG's development mission. Within ITS, the Fiduciary Operations unit (ITSFD) is responsible for digital solutions that support Procurement, Financial Management, and Environmental and Social Safeguards across World Bank operations. About the Team: E S (Environmental Social) This internship program is hosted by the E S (Environmental Social) team, the product and technology team within ITSFD responsible for building and maintaining the digital systems that support the World Bank Group's environmental and social risk management and accountability functions. The E S product team builds the tools that both groups, along with task teams and safeguards specialists across the Bank, rely on daily track and manage workflows, and report on E S risk and compliance. Interns will gain hands-on exposure to how the Bank manages environmental and social risk, complaints, and incident tracking across its global project portfolio. Depending on their track, they'll build skills in requirements gathering, applied AI/ML for risk classification and case triage, or data engineering, all while contributing to tools that support accountability and protect communities affected by Bank-financed projects. Duties and Responsibilities Support the design, development, and testing of AI/ML models to support E S case triage, risk classification, or analytics use cases. Assist in data preparation, feature engineering, and model evaluation using structured and unstructured data from case management systems. Contribute to proof-of-concept work exploring generative AI and automation opportunities within E S workflows. Collaborate with data engineers and product owners to translate business problems into data science solutions. Document methodologies, model performance, and findings for technical and non-technical audiences.