The Monitoring and Evaluation (M&E) Associate for Rapid Experimentation will support the execution and analysis of A/B tests across GiveDirectly’s programs, contributing to the use of data to inform program and product decisions. This role is fast-paced and iterative - the team runs frequent, lightweight experiments designed to generate actionable answers quickly, and then uses those learnings to refine and improve programs in real time.
Core Responsibilities
Execute and manage A/B tests across programs
Conduct power calculations to ensure experiments are both statistically rigorous and feasible to implement within program constraints.
Set up pre-specified experimental designs, applying defined experimental groups, outcome measures, and measurement timelines.
Review experiment setups prior to launch and flag execution and measurement risks that may affect interpretability.
Ensure experiments are well-coordinated and executed as designed, aligning implementation with research plans and integrating smoothly into program delivery across Programs and Product teams.
Work at a fast pace across a portfolio of 2–3 live A/B tests at any given time, designed to generate actionable answers quickly and feed rapid iteration of programs and products.
Ensure accurate measurement and high-quality data for experiments
Collaborate with external Principal Investigators (PIs) to ensure measurement approaches and data collection are aligned with research design and implementation realities.
Ensure experimental outcomes are captured accurately and consistently by applying established indicator and measurement approaches.
Prepare and manage datasets that are clean, well-structured, and ready for analysis using survey, administrative, and product data.
Identify and flag data quality risks (e.g., missingness, inconsistencies, measurement error) that could affect the validity of experimental conclusions.
Conduct targeted literature reviews to ensure measurement approaches are grounded in evidence and aligned with best practices.
Analyze experimental data and interpret results to inform decisions
Generate reliable and decision-ready analyses of experimental data from A/B tests.
Assess the magnitude and direction of effects and highlight what the results do and do not suggest, noting key limitations.
Ensure results are clearly understood and appropriately interpreted, given data quality, sample size, and implementation considerations.
Translate results into actionable insights and learning across experiments
Translate experimental results into clear, actionable recommendations to guide program and product decisions for individual country programs, and for the direction of GiveDirectly’s programming as a whole.
Structure results and key learnings so they can be reused to inform future experiments and program design.
Prepare concise learning products (e.g., memos, summaries) that serve multiple audiences, including internal Programs and Product teams, and external academic partners.
Prepare and clean de-identified datasets for sharing with external PIs and academic partners, ensuring data is structured, well-documented, and ready for independent analysis.
Contribute to cross-country discussions to ensure learnings from experiments are shared and applied across contexts.
Requirements
Bachelor’s degree (or equivalent) in Economics, Statistics, Public Policy, or a related quantitative field.
2–4 years of experience working with data in applied settings (e.g., experimentation, evaluation, analytics, or program learning), ideally in development, tech, or operations-focused roles.
Solid understanding of experimental design and causal inference concepts (e.g., randomization, treatment/control groups, units of randomization, statistical power, bias) and how to apply them in real-world program contexts.
Experience using R, Python, or Stata to clean, manipulate, and analyze data, including working with multiple data sources (e.g., survey or administrative data).
Experience collaborating with cross-functional teams (e.g., programs/operations, product, or research) and external partners to implement projects and solve problems.
Fluency in English required.
Comfort working at pace - able to manage multiple workstreams simultaneously, make progress with imperfect data, and iterate quickly based on emerging findings.
Ability to interpret results beyond statistical significance and communicate clear, actionable insights to both technical and non-technical audiences.
Travel and Location
This role is fully remote. Travel within East Africa is a regular part of the role, estimated at up to 25% of the time, to support field operations across country programs. Additional international travel may occur for trainings or team convenings (estimated up to 10%).
Interested and qualified candidates should apply online through the Greenhouse portal linked from the MyJobMag page: GiveDirectly Application Link which redirects to job-boards.greenhouse.io.
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