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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Scientist (Evaluation) - **Company:** GEF, INC. - **Location:** Leavenworth, WA, United States - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Clean Code Principles, Geographic Information Systems, Application Programming Interfaces (APIs), Artificial Intelligence, ArcGIS (Software), Computer Simulation, Computer Programming, Databases, D3.Js, Data Systems, Data Visualization, Programming Tools, R (Programming Language), Information Extraction, Information Management, Interoperability, Python (Programming Language), Machine Learning, Automation of Marketing, Metadata, Natural Language Processing, Programming Environments, Quantum GIS (QGIS), Power BI, SQL Databases, Systems Integration, Tableau (Software), Large Language Models, Prompt Engineering, Topic Modeling, Information Technology, Data Management - **Published:** October 18, 2026 - **Apply:** https://www.dice.com/job-detail/a0237948-e46c-44fa-8b6b-35fa47a94053 ## About the Role Master's degree in computer science, data science, statistics, economics, information management, environmental sciences, public policy, finance, business administration, or another relevant discipline with a strong quantitative and analytical component. Advanced training in statistics, econometrics, programming, machine learning, or related computational methods is required. A PhD or equivalent advanced research experience would be an advantage. At least five years of relevant professional experience applying data science, advanced analytics, artificial intelligence, machine learning, or related computational methods to complex research, evaluation, policy, or development questions, including experience with large and heterogeneous datasets and reproducible analytical workflows. Demonstrated experience applying AI and machine learning frameworks, including natural language processing, large language models and prompt engineering, topic modelling, information extraction, classification, or related approaches. Ability to assess the validity, limitations, and appropriate use of AI-generated or computational evidence is essential. Demonstrated ability to independently design analytical approaches, translate research or evaluation questions into appropriate quantitative and computational methods, and integrate evidence across data sources and methodological approaches. Experience evaluating environmental, climate, biodiversity, or sustainable-development interventions would be an advantage. Strong conceptual, research, and analytical skills, including the ability to interpret complex findings, identify their policy and evaluation significance, and communicate methodological limitations clearly. Experience with geospatial analysis and GIS platforms such as QGIS or ArcGIS and/or programmatic geospatial analysis is highly desirable. Experience integrating remote-sensing, geospatial, socioeconomic, and other data sources would be an advantage. Advanced proficiency in Python, R, SQL, or comparable programming environments, with demonstrated experience in databases, data-management systems, APIs, and reproducible analytical workflows. Strong proficiency in data visualization and communication using Tableau, Power BI, D3.js, or comparable tools, with the ability to communicate complex analytical results effectively to technical and non-technical audiences. Demonstrated ability to provide technical guidance and quality assurance to multidisciplinary teams and contribute to methodological standards, guidelines, or institutional analytical practices. Excellent interpersonal skills and ability to collaborate effectively across disciplines, institutions, countries, and cultures and build productive relationships with internal and external technical partners. Excellent written and oral communication skills in English, including the ability to prepare high-quality analytical and methodological products and present complex technical findings clearly. Knowledge of an additional language, such as Chinese, French, Spanish, or Portuguese, is a plus. Proven ability to manage multiple complex assignments with substantial autonomy, exercise sound judgment in setting priorities and resolving analytical problems and deliver high-quality results within agreed objectives and deadlines. ## Description Lead the development, management, integration, and analysis of complex datasets from multiple internal and external sources to support IEO evaluations and analytical work. Develop robust, reproducible, and maintainable code, analytical pipelines, and data systems, ensuring appropriate standards for data quality and documentation. Design and apply artificial intelligence and advanced data-science approaches to extract, process, integrate, and analyze information from large and heterogeneous sources, including reports and other published and unpublished documents, administrative data, metadata, geospatial information, and other structured and unstructured sources. Translate evaluation questions into appropriate computational approaches and assess the robustness and limitations of the resulting evidence. Develop, test, and adapt state-of-the-art machine learning and AI techniques to the analytical requirements of IEO and the GEF. Lead experimentation with approaches that integrate multiple sources and data types, including text, satellite imagery, geospatial data, and geo-referenced socioeconomic and environmental databases, and assess their potential for application across evaluations. Provide substantive methodological and technical inputs to IEO evaluations, identifying opportunities where AI, machine learning, geospatial analysis, and other data-science methods can strengthen evaluation design, evidence collection, triangulation, and analysis. Work with evaluation teams to ensure that advanced methods respond to evaluation questions and that results are appropriately interpreted within their institutional, socioeconomic, and environmental contexts. Establish and maintain effective working relationships with data producers, curators, engineers, researchers, and technical partners within and outside the GEF and World Bank Group. Represent IEO in relevant technical exchanges and communities of practice and identify opportunities for collaboration, methodological innovation, and access to new data and expertise. Contribute to open and reproducible solutions for data documentation, cataloguing, management, and dissemination, promoting good practice in data curation, metadata, interoperability, transparency, and reproducibility. Design and oversee dashboards, interactive analytical products, and advanced visualizations using appropriate platforms and programming tools. Develop technical guidelines, methodological protocols, reference materials, and training resources for the application of data science, AI, machine learning, and geospatial approaches to evaluation, supporting their responsible adoption and institutionalization within IEO. Lead analytical working papers and technical studies supporting IEO evaluations, including methodological design, quantitative and computational analysis, interpretation of findings, preparation of visualizations, and presentation of results and methodological limitations. Undertake other analytical and methodological assignments as required, exercising independent judgment in defining approaches, resolving complex technical issues, and delivering high-quality outputs within agreed objectives and timelines.