Job Description

E T Consultant

Job #:
req37477
Organization:
World Bank
Sector:
Economics
Grade:
EC1
Term Duration: 1 year 0 months
Recruitment Type:
Local Recruitment
Location:
Washington, DC,United States
Required Language(s):
English
Preferred Language(s):
Closing Date:
8/22/2026 (MM/DD/YYYY) at 11:59pm UTC

Do you want to build a career that is truly worthwhile? The World Bank Group is a unique global partnership of five institutions driven by a bold vision to create a world free of poverty on a livable planet. As one of the largest sources of funding and knowledge for developing countries, we help solve the world’s greatest development challenges. When you join the World Bank Group, you become part of a dynamic, diverse organization with 189 member countries and more than 120 offices worldwide. We work with public and private sector partners, invest in groundbreaking projects, and use data, research, and technology to bring tangible and transformative change around the globe. For more information, visit www.worldbank.org.

The Development Economics Vice Presidency (DEC) is the World Bank’s central reservoir of fresh insights into the most pressing challenges of development. It is led by the Chief Economist and Senior Vice President of the World Bank Group, who advises the President and senior managers, serves as the community leader for the WBG’s economists, and helps to keep the institution in the forefront of thinking about development policy. DEC constitutes one of the world’s largest teams of economists focused on policy solutions for developing economies.

Hosted within the Office of the Chief Economist, People Vertical, the Strategic Impact Evaluation Fund (SIEF) is a multi-donor trust fund launched in March 2012 to strengthen results-focused monitoring and evaluation in order to improve the effectiveness of development policies for human development outcomes. To support and promote evidence-based policymaking, SIEF is developing the Impact Data and Evidence Aggregation Library (IDEAL), an open-access platform of randomized controlled trials (RCTs) of social sciences in low- and middle-income countries.

The IDEAL pilot has developed tools supporting data extraction, quality assurance, and evidence screening, including machine learning-based classifiers and automated search systems. These tools aim to improve the accuracy, consistency, and efficiency of evidence aggregation at scale. To continue and expand this work, SIEF is seeking a Junior Data Scientist (Extended Term Consultant) to contribute to ongoing tool development, research validation, and potential collaboration with the World Bank Data Group on relevant data products.

Duties and accountabilities

The consultant will be responsible for the following tasks:

1. Survey Platform Development and Maintenance
• Maintain and further develop the custom coding platform built to support IDEAL's human coding and quality assurance workflows.
• Identify and implement enhancements to improve platform usability, stability, and performance based on user feedback. Maintain the technical documentation of each major version that is suitable for future development.
• Support the integration of the external survey platform into the WBG Cloud Infrastructure, following the security accreditation process from the Office of Information Security (OIS).

2. Data Engineering and Management
• Design and build a relational database that organizes IDEAL's extracted data from the survey platform across multiple interconnected datasets (e.g., study characteristics, outcomes, interventions, sample, effect sizes), following best practices in database normalization and documentation.
• Develop and maintain data pipelines that automate the export, transformation, and validation of data flowing from the survey platform into the relational database, minimizing manual handling.
• Establish and enforce data quality standards, including validation rules, consistency checks, and version control protocols, to ensure the integrity of the relational datasets over time.
• Design and develop a public-facing inquiry system that allows external users including researchers, policymakers, and development practitioners to search, filter, and access IDEAL's data. The system should be intuitive, well-documented, and aligned with open-access principles.

3. Machine Learning and LLM-Based Study Classifier
• Maintain and improve the existing machine learning and LLM-based models that classify published research by methodology, study topics, measured outcomes, and other indicators that meet the project needs.
• Conduct validation exercises to assess and document model accuracy, recall, and sensitivity across different search contexts and disciplines.
• Explore extensions of the classifier to support additional use cases, such as topic modelling.

4. Data Extraction Automation
• Design, develop, and iterate on machine learning- or AI-based automation tools to facilitate the data extraction process within the IDEAL pilot, reducing reliance on manual coding where feasible.
• Work closely with the IDEAL team to identify priority extraction fields and iteratively refine tools based on user feedback and extraction performance.
• Support the development of validation protocols to assess the accuracy and reliability of automated extraction outputs relative to human coder benchmarks.
• Ensure that automation tools are designed with transparency and reproducibility in mind, with clear documentation of model choices, prompting strategies, and known limitations.

Selection Criteria

Candidates will be evaluated based on the following criteria:

• Academic Background: A master’s degree in computer science, data science, statistics, economics, or a related quantitative field is required, with at leas two years of relevant experience.
• Programming and Software Development: Proficiency in programming languages and software is required. Candidates should demonstrate the ability to build and maintain functional software tools, including web applications, APIs, or data pipelines.
• Data and Database Management: Experience working with relational databases and SQL is expected, along with familiarity with structuring and managing research or administrative data in clean, reproducible formats.
• Machine Learning and AI: Candidates should have hands-on experience with machine learning frameworks and LLM-based tools, with evidence of applying these to real-world classification, extraction, or automation tasks.
• Research and Evidence Synthesis Experience: Prior experience with systematic reviews, meta-analyses, RCT-based research, or evidence aggregation workflows is an advantage. Familiarity with academic publishing and research methodology is desirable.
• Communication and Documentation: Candidates should be able to document technical work clearly for both technical and non-technical audiences, with strong written English and a demonstrated ability to prepare technical notes, reports, or user guides.
• Collaboration and Initiative: Evidence of working effectively in team settings, engaging with multiple stakeholders, and taking ownership of tasks with limited supervision is expected.

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.

World Bank Group Core Competencies

As per WBG policy, an Extended Term (ET) appointment is subject to a lifetime maximum of three (3) years. Former and current ET staff who have completed or are in the process of completing their third-year ET appointment are not eligible for future ET appointments.

We are proud to be an equal opportunity and inclusive employer with a dedicated and committed workforce, and do not discriminate based on gender, gender identity, religion, race, ethnicity, sexual orientation, or disability.

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