Overview
The World Bank Group's Women, Business and the Law project is seeking a Data Analysis Intern to examine laws and regulations affecting women's economic inclusion. The intern will contribute to data preparation, analysis, and AI integration to inform policy discussions.
Key Responsibilities
- Clean, validate, and reconcile large, multi-source datasets, identifying and correcting errors.
- Develop and apply systematic processes to standardize, map, and reconcile data.
- Prepare API-ready data outputs, including JSON files.
- Develop and implement data-cleaning protocols, validation rules, and automated quality checks.
- Conduct data audits and produce monitoring and quality-assurance reports.
- Analyze data to identify trends, patterns, and actionable insights.
- Prepare analytical, progress, and monitoring reports using tools such as Excel or Python.
- Present findings clearly to technical and non-technical audiences.
- Pilot AI-powered workflow to enhance data quality, integrity, and operational efficiency.
- Conduct AI-driven analysis to support data validation and insights generation.
- Establish monitoring and evaluation mechanisms to track AI model performance.
- Ensure transparency and documentation of AI workflows.
- Suggest ways to automate verification of survey responses.
- Identify and mitigate risks related to bias, accuracy, and reliability of AI-generated outputs.
- Interpret complex datasets and develop clear, intuitive visualization concepts.
- Develop prototypes, mock-ups, and data visualization products using tools such as Tableau, Flourish, Power BI, or similar platforms.
Required Experience
- Experience using AI-assisted workflow to conduct legal research is a strong plus.
- Experience integrating AI solutions to improve system automation is preferred.
- Demonstrated ability to analyze data, translate findings into actionable insights, and communicate results to technical and non-technical audiences.
- Strong attention to detail, initiative, and the ability to work independently while managing multiple priorities.
Qualifications
A master’s candidate in data analytics, data science, statistics, computer science, machine learning, artificial intelligence, information technology, or an equivalent field.
