Priority Application Deadline: May 15, 2026

About this role

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. This includes:

• Supporting the execution and analysis of rapid A/B tests across GiveDirectly projects, ensuring that experiments are implemented effectively and contribute to learning within and across projects
• Ensuring experiments are implemented correctly, measured reliably, and analyzed to produce clear and credible results, working closely with Programs, Product, Research teams, and external academic partners to align experimental design with program delivery, data collection, and operational realities
• Translating findings into actionable insights and well-structured learning products that serve multiple audiences - internal program and product teams, and external academic partners, ensuring results inform both immediate decisions and longer-term program direction

In practice, this role is about managing a high volume of rapid experiments and turning results into clear, credible evidence that continuously shapes how GiveDirectly’s programs are refined and improved.

Reports to: Senior Manager, Monitoring and Evaluation

Level: Associate

Travel Requirement: This role is based in Rwanda. 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, as needed (estimated up to 10%)

What you’ll do:

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, ensuring findings are clearly communicated for both technical and non-technical stakeholders 
• 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, and maintain clear documentation so experiments are easy to track, understand, and build on over time

What you’ll bring:

• Exceptional alignment with GiveDirectly Values and active demonstration of our core competencies: emotional intelligence, problem-solving, project management, follow-through, and fostering inclusivity. We welcome and strongly encourage applications from candidates who have personal or professional experience in the low-income and/or historically marginalized communities that we serve.
• 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

Compensation

At GiveDirectly, we strive to pay our employees generously and equitably. We use an accredited third party salary aggregator to calculate what we believe to be competitive pay based on role, location, and cost of living. We also have a no negotiation policy to ensure we are paying staff equitably across roles. Read more about our compensation philosophy here.

Unless otherwise noted, the benefits stipend may be used to cover benefits or taken as additional taxable income.

Kenya

• Base Salary: $42,000
• Bonus at Target Performance: 10% (~$4,200, with potential for upside. For reference, with the organization's current performance multiplier, this amount would be $4,914 in 2025)
• Estimated Total Compensation at Target: $46,200+

Rwanda

• Base Salary: $37,600
• Bonus at Target Performance: 10% (~$3,760, with potential for upside. For reference, with the organization's current performance multiplier, this amount would be $4,399 in 2025)
• Estimated Total Compensation at Target: $41,360+

This role is fully remote, so if you are not based in Kenya or Rwanda, we will share an estimated salary benchmark for the country you are based in during the hiring process. 

Why work at GiveDirectly?

At GiveDirectly, we work to ensure that you have everything you need to excel in your role and on your team, including:

• 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

 #LI-REMOTE

About One Acre Fund

Founded in 2006, One Acre Fund equips 5.5 million smallholder farmers to make their farms more productive. Across nine countries that together are home to two-thirds of Africa's farmers, we provide high-quality farm supplies, tree seedlings, accessible credit, modern agronomic training, and a wide range of other agricultural services. On average, this model enables any farmer to increase their income and assets on supported land by more than 35 percent, while permanently improving their resilience. This is all made possible by our team of 9,000+ full-time staff, drawn from diverse backgrounds and professions. To learn more, please see our Why Work Here blog post.

About the Role

From R&D to sales to strategy to operations, the Global R&D Data Analyst has the unique opportunity to improve decision-making across all aspects of One Acre Fund’s program using many diverse data types, such as sales, yield, demographic and satellite data, to help us reach more farmers with greater impact. 

The Global R&D Data Analyst will help us reach over one million farmers by executing analyses for strategic decision-making on repayment, expansion, and other business functions, and work directly with program leaders to interpret results and make data-driven decisions. The Global R&D Data Analyst will play an integral role in shaping One Acre Fund’s data strategy, including dreaming up and executing new ways to use our data to improve our program.

Additionally, One Acre Fund has a robust agronomic and socioeconomic research program spanning all countries of operation. This role will work closely with country R&D teams to ensure all trials are executed at the highest possible standards, provide follow-up analytical support and training to team members, and support with warehousing of our agronomic data to make our research outputs accessible to external collaborators, further increasing One Acre Fund’s smallholder farmer impact across the continent.

To succeed in this role, you will need to be a strong communicator and have a solid analytical background with experience in experimental design. You will need to be comfortable interpreting ambiguous results generated with imperfect data and advising leaders on the relative risk associated with different decisions based on the results of your analysis. 

This is a deliberately hybrid role. Success requires the ability to operate effectively as:

• an experimental methodologist (trial design & causal inference),
• an applied data scientist (production analytics, geospatial methods, modelling), and
• a delivery-oriented project manager (prioritisation, documentation, coordination).

Responsibilities

Own methodological rigour and analytical quality for trials and surveys (30%):

• Design and analyse trials and surveys, including:
  • Sample size and power calculations
  • Stratification and experimental design
  • Recommend the appropriate statistical methods (e.g., hypothesis testing, regression, ANOVA/mixed models)
• Lead analysis of agronomic and product trials to estimate treatment effects and program impact
• Quality assure trial designs and analyses produced by other analysts
• Translate trial findings into clear recommendations for product design, agronomic guidance, and program strategy.

Develop scalable analytical products and decision-support tools using program, survey, and spatial data (30%):

• Build, maintain, and improve analytical pipelines and production codebases that power operational decision tools (e.g., sowing date or input recommendations), including occasional support at the production level.
• Integrate survey, MEL, and operational data with geospatial layers (soil, climate, vegetation, remote sensing) to generate localised recommendations and program targeting strategies.
• Conduct spatial and remote-sensing analyses for program design, prioritisation, and impact estimation (e.g., soil erosion modelling, site suitability analysis).
• Analyse historical trial and soil data to generate input and soil management recommendations (e.g., lime application, fertiliser rate application).
• Evaluate potential impact of alternative interventions and support pilot design, iteration, and scale decisions.
• Translate analyses into decision-ready outputs (briefs, dashboards, and memos) for non-technical stakeholders.
• Identify new, high-leverage analytical use cases that improve program reach, impact, or cost-effectiveness.

Lead impact data management and project management (~20%)

• Lead curation and standardisation of historical yield, agronomic practice, and trial datasets to enable reuse and external research collaboration.
• Own knowledge management for impact data and trials, including:
  • Central documentation of methodologies, assumptions, sample sizes, and results for all projects
  • Reusable analysis templates and reference implementations
• Manage external data requests in compliance with client data protection and confidentiality protocols.

Provide portfolio-level project management (~20%):

• Maintain project plans, priorities, and timelines
• Track dependencies and risks
• Coordinate with program and R&D stakeholders to identify potential delivery risks
• Establish durable documentation and planning systems (e.g., project roadmaps, project trackers, shared repositories).

Career Growth and Development

We have a strong culture of constant learning, and we invest in developing our people. You’ll have weekly check-ins with your manager, access to mentorship and training programs, and regular feedback on your performance. We hold career reviews every six months and set aside time to discuss your aspirations and career goals. You’ll have the opportunity to shape a growing organization and build a rewarding long-term career.

Qualifications

Across all roles, these are the general qualifications we look for. For this role specifically, you will have:

• Bachelor's Degree in one of the following fields: economics, econometrics, mathematics, or statistics
• Proficiency in R and/or Python, including working knowledge of -
• Database connectivity (e.g., PostgreSQL) to enable data retrieval, manipulation, and storage from various databases
• Interact with RESTful APIs (e.g., JSON, XML)
• Data manipulation libraries (e.g., dplyr, tidyr) for efficient data wrangling, transformation, and exploration
• Packages for data visualisation (e.g., ggplot2, lattice, plotly)
• Advanced statistical analysis and modelling (stats, lme4, survival)
• Machine learning frameworks (e.g., randomForest, xgboost, caret) for building predictive models and conducting machine learning tasks
• Packages for data manipulation and visualisation, such as numpy, pandas, and Matplotlib
• Spatial data manipulation libraries (geopandas, rasterio, shapely, GDAL)
• In-depth knowledge of statistically rigorous trial design methodologies, including RCTs, side-by-side comparisons, RCBD, and other experimental designs
• In-depth knowledge of statistically rigorous survey design methods, including random, stratified, and cluster sampling
• Knowledge of relevant meteorological, soil, and vegetation data layers and sources, their uses and limitations (e.g., iSDA, ISRIC, CHIRPS, TAMSAT, NASA, Sentinel Hub, Google Earth Engine, AWS)
• Working knowledge of agronomy, e.g., practical understanding of fertiliser nutrient compositions, plant populations, growing degree days, GxE interactions.
• Working knowledge of GIS tools such as ArcGIS and QGIS, and spatial data analysis techniques.
• Proficiency in version control, such as Git/GitHub.
• Ability to easily explain technical concepts to non-technical decision makers and grow the analytical skills of others.
• Excellent written and verbal communication skills for coordinating across teams.
• Demonstrated ability to manage multiple analytical projects in parallel, including:
• Scoping ambiguous analytical problems and translating them into deliverable plans
• Prioritising work against timelines and stakeholder needs
• Tracking progress, managing dependencies, and proactively unblocking delivery risks
• Maintaining clear documentation and project plans to ensure continuity and institutional memory

Preferred Start Date

As soon as possible

Job Location

Nairobi, Kenya or Kigali, Rwanda

Benefits

Health insurance, housing, and comprehensive benefits

Contract Duration

2 Years

Eligibility

One Acre Fund can support a work permit for this role. However, nationals of (or those with an extensive professional background and work history in) our countries of operation are preferred.

Application Deadline

10 July, 2026

Please note that we hire on a rolling basis, which means that applications are reviewed and processed on a continuous basis until a hire is made.

One Acre Fund never asks candidates to pay any money or pay for tests at any stage of the interview process. Official One Acre Fund emails will always arrive from an @oneacrefund.org address. Please report any suspicious communication here (globalhotline@oneacrefund.org), but do not send applications or application materials to this email address.

Diversity, Equity, Inclusion (DEI), and anti-racism are deeply connected to our organisation’s mission and purpose. One Acre Fund aspires to build a culture where all staff feel consistently valued, represented, and connected – so that our team can thrive as professionals, and achieve exceptional impact for the farmers we serve.

We are committed to equal employment opportunity regardless of race, colour, ancestry, religion, sex, national origin, sexual orientation, age, marital status, disability, gender, gender identity or expression. We are proud to be an equal opportunity workplace.