Data Scientist

Job #:
req38327

Organization:
World Bank Group

Sector:
Knowledge Management

Grade:
GF

Term Duration:
Open-Ended Staff (OPEN-OP)

Recruitment Type:
International Recruitment

Location:
Washington, DC,United States

Required Language(s):
English

Preferred Language(s):

Closing Date:
10/5/2026 (MM/DD/YYYY) at 11:59pm UTC

Description

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.

Selection Criteria
• Master's degree in data science, computer science, statistics, economics, applied mathematics, or a related quantitative field, with a minimum of five years of relevant professional experience.
• Strong applied experience in machine learning and natural language processing (NLP), including text classification, semantic embeddings and search, information extraction, or related analysis of large unstructured text collections.
• Demonstrated experience using large language models (LLMs) programmatically for classification, extraction, structured analysis, or similar analytical tasks, including prompt design, systematic validation, and understanding of the limitations of generative AI.
• Advanced proficiency in Python and SQL, with strong skills in data management, statistical analysis, data visualization, version control, and reproducible analytical workflows; experience with Databricks/Spark or similar is desirable.
• Strong grounding in quantitative research methods and model evaluation, including sampling and validation, precision/recall trade-offs, error analysis, confidence assessment, and rigorous interpretation of analytical results.
• Demonstrated ability to translate complex management and operational questions into tractable analytical approaches. Experience with operationalizing ontologies into analytics is desirable.
• Demonstrated ability to synthesize and visualize findings across sectors, countries, datasets, and analytical methods for technical and non-technical audiences. Experience with interactive data visualization tools and libraries is desirable.
• Strong initiative, results orientation, and teamwork skills, with the ability to work effectively across multidisciplinary teams and evolving priorities. Experience with user-facing system and analytical product design, interoperability with APIs and data schemas, development finance, MDB operational data, vector databases/RAG and retrieval systems, or LLM agent engineering would be an advantage.

As the World Bank Group continues to evolve, we value candidates who:

• Demonstrate the ability to collaborate effectively across teams, disciplines, cultures, and institutional boundaries.
• Responsibly leverage digital and AI-enabled tools to enhance productivity, learning, and decision-making.
• Bring experience working in fragile, conflict-affected, and violent (FCV) contexts and are encouraged to highlight relevant experience in their application materials, where applicable.

WBG Culture Attributes:

1. Sense of urgency: Anticipate and quickly respond to the needs of internal and external stakeholders.
2. Thoughtful risk-taking: Challenge the status quo and push boundaries to achieve greater impact.
3. Empowerment and accountability: Empower yourself and others to act and hold each other accountable for results.

The World Bank Group offers comprehensive benefits, including a retirement plan; medical, life and disability insurance; and paid leave, including parental leave, as well as reasonable accommodations for individuals with disabilities.

Learn more about working at the World Bank and IFC including our values and inspiring stories.