Global Research and Data Science

The Global Research and Data Science (GRDS) Unit at IPA build tools and data systems that enable high-quality data collection and application of data science methods to improve research efficiency and replicability grounded in ethical principles.

The Global Research and Data Science (GRDS) Unit at Innovations for Poverty Action (IPA) drives innovation through the development of data systems, tools, and methodologies that make evidence generation and use more efficient, ethical, and scalable. The team works across IPA and with external partners to design ethical, scalable data systems and solutions that strengthen how evidence informs programs and policies.

GRDS operates across five main service areas. Each area encompasses specific capabilities and applications.

Data Products & Infrastructure

Attribute Details
Function Design secure, interoperable, and scalable data systems for research teams and partners

Capabilities:

  • Data pipelines and ETL/ELT automation
  • Cloud-based data warehouses and layered architectures
  • Dashboards and visualization systems
  • API integration and interoperability between platforms
  • Metadata management and version control

Applications:

  • Build end-to-end data pipelines connecting survey, administrative, and external data sources
  • Design architectures for data cleaning and validation
  • Develop interactive dashboards for program monitoring and decision-making
  • Automate metadata documentation and update tracking

Data Science & Engineering

Attribute Details
Function Apply data science and analytical methods to derive insights, automate workflows, and improve decision-making

Capabilities:

  • Predictive modeling and forecasting
  • Natural Language Processing (text, chat, or document data)
  • Geospatial and image analysis
  • Automation and quality assurance systems
  • Experimental design and adaptive trials

Applications:

  • Predict student or household outcomes using ML models
  • Automate real-time survey data validation pipelines
  • Extract insights from open-ended and administrative text
  • Combine geospatial and socioeconomic data for targeting
  • Design adaptive sampling frameworks to optimize fieldwork

Research Knowledge & Methods

Attribute Details
Function Promote and generate methodological resources that strengthen rigor, reproducibility, and learning

Capabilities:

  • Power calculations and sample design
  • Reproducibility checks and code review
  • Development of standardized templates and analytical pipelines
  • Methodological documentation and learning resources
  • Meta-analysis and synthesis of research findings

Applications:

  • Provide power and sample size calculations for research designs
  • Create and improve open-source resources and templates for research processes
  • Conduct reproducibility and code quality reviews across projects
  • Develop methodological guidance and training materials for research teams

Ethics & Responsible Data

Attribute Details
Function Integrate ethics, privacy, and responsible data practices into every stage of research
IRB IPA’s Institutional Review Board provides independent ethical oversight for studies conducted, managed, or funded by IPA across low- and middle-income countries

Capabilities:

  • IRB coordination and reliance agreements
  • Data protection and privacy risk assessments
  • Governance and compliance frameworks
  • Responsible data audits and ethical reviews
  • Training on responsible data collection and use

Applications:

  • Oversee IRB review and approval processes for IPA-led and partner studies
  • Design privacy-by-design protocols and anonymization workflows
  • Conduct risk assessments for digital and administrative data use
  • Build institutional capacity in ethical research and responsible data management

Capacity Building

Attribute Details
Function Strengthen institutional and local capacity through tailored training, technical mentorship, and system-strengthening initiatives

Capabilities:

  • Data science and analytics training programs
  • Mentorship and technical support for research staff
  • Knowledge-sharing tools and documentation
  • Institutional data governance and sustainability support
  • Learning pathways for technical upskilling

Applications:

  • Deliver Python, GitHub, and data management trainings for research and policy teams
  • Develop onboarding and learning resources for new projects and partners
  • Mentor field and data teams through project-based learning models
  • Design institutional capacity assessments and roadmaps for improvement
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