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Data Scientist
Data Science
Posted on Sep 19, 2026
At 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 www.worldbank.org VPU Context: The WBG is in the midst of a significant institutional transformation. The Bank unified its knowledge and financial systems to accelerate impact, boost efficiency, and deliver greater value to clients, bringing together experts from across the institution to supercharge thought leadership and to replicate and scale what works with public and private sector clients. This transformation came into effect on January 1, 2026, advancing the WBG Knowledge Bank as an institution-wide agenda to which all staff contribute, supported by an integrated platform spanning the World Bank, IFC, and MIGA that is designed to systematically capture, curate, and deliver the latest development insights, research, and innovations to clients. The Partnerships, Innovation, and Mobilization Vice Presidency (PIM) is a newly established World Bank Group Vice Presidency that brings together the institution’s work on IDA policy and resource mobilization, partnerships, trust funds, financial intermediary funds (FIFs), co-financing, and innovation. PIM plays a central role in strengthening development partnerships, mobilizing development finance at scale, supporting IDA implementation, and accelerating the WBG’s innovation pipeline. The Department for Innovation develops and pilots new initiatives and drives forward-thinking approaches to address complex development challenges facing the world today. It does so by surfacing and accelerating early-stage innovations that tackle complex and persistent development issues through the WBG Innovation Awards, unlocking the WBG's collective innovation intelligence through the Global Knowledge Platform (The Innovation Portfolio for Development Outcomes P513924), mainstreaming transformative capabilities such as geospatial intelligence to strengthen development decision-making, fostering a culture of innovation within the Bank, collaborating with external partners and across the WBG to tap into expertise, and spreading successful innovation to transform future Bank engagements. The Data Scientist who will lead the design and implementation of advanced data analytics frameworks, support the development of data-driven innovation strategies, and build internal capacity for evidence-based decision-making. Duties and accountabilities: The Data Scientist will undertake the following activities: •Operationalize and continuously improve the Innovation Analytics methodology – an AI- and ML-enabled approach to identify, classify, and analyze innovation across WBG portfolios. Combine ontology-based concepts, semantic embeddings, LLM-assisted analysis, natural language processing (NLP), and other statistical and machine-learning methods over the structured and unstructured operational and knowledge data. •Build reproducible data and analytical pipelines for document ingestion, text extraction, sub-component-level innovation detection, lifecycle and maturity classification, replication and diffusion analysis, and portfolio-level aggregation. •Design and implement rigorous validation and quality-assurance approaches, including expert validation, sampling, error analysis, confidence assessment, comparison across analytical methods, and monitoring of false positives and false negatives. •Apply the methodology to country, sector, thematic, Trust Fund, IDA, and other WBG use cases, translating management questions into appropriate datasets, analytical approaches, and decision-relevant outputs. •Develop clear analytical products and visualizations that identify portfolio patterns, replication and scaling opportunities, capability gaps, and other strategic insights for operational teams and senior management. •Document analytical methods, data transformations, assumptions, validation results, limitations, and methodology changes, and contribute to progressively standardizing and scaling the Innovation Analytics service.