[Hiring] M&E Associate - Rapid Experimentation @GiveDirectly

Role Description

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.

• Support the execution and analysis of rapid A/B tests across GiveDirectly projects.
• Ensure experiments are implemented correctly, measured reliably, and analyzed to produce clear and credible results.
• Work closely with Programs, Product, Research teams, and external academic partners to align experimental design with program delivery, data collection, and operational realities.
• Translate findings into actionable insights and well-structured learning products for multiple audiences.
• Manage a high volume of rapid experiments and turn results into clear, credible evidence that continuously shapes how GiveDirectly’s programs are refined and improved.

Qualifications

• Exceptional alignment with GiveDirectly Values and active demonstration of core competencies: emotional intelligence, problem-solving, project management, follow-through, and fostering inclusivity.
• 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).
• Solid understanding of experimental design and causal inference concepts.
• Experience using R, Python, or Stata to clean, manipulate, and analyze data.
• Experience collaborating with cross-functional teams and external partners.
• Fluency in English required.
• Comfort working at pace, managing multiple workstreams simultaneously.
• Ability to interpret results beyond statistical significance and communicate clear, actionable insights.

Requirements

• Execute and manage A/B tests across programs.
• Conduct power calculations to ensure experiments are statistically rigorous and feasible.
• 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.
• Ensure experiments are well-coordinated and executed as designed.
• Work at a fast pace across a portfolio of 2–3 live A/B tests.
• Ensure accurate measurement and high-quality data for experiments.
• Collaborate with external Principal Investigators (PIs) to ensure alignment with research design.
• Prepare and manage datasets that are clean, well-structured, and ready for analysis.
• Identify and flag data quality risks that could affect validity.
• Conduct targeted literature reviews to ensure measurement approaches are grounded in evidence.
• Analyze experimental data and interpret results to inform decisions.
• Generate reliable and decision-ready analyses of experimental data.
• Translate results into actionable insights and learning across experiments.
• Prepare concise learning products for multiple audiences.
• Prepare and clean de-identified datasets for sharing with external PIs and academic partners.
• Contribute to cross-country discussions to ensure learnings are shared and applied.

Benefits

• A supportive team that works hard and cares hard.
• A robust health benefits plan (exact details will vary by country).
• Flexible paid time off that staff is encouraged to take.
• Allowances for desk set-up and learning and development.