MEL & Research Manager

About Digital Green

About the role

What you will do

Design research and measurement for FarmerChat

• Support the design and implementation of MEL studies and evaluations that assess FarmerChat’s reach, engagement, user experience, behavior change, and outcomes for farmers.
• Translate program and product questions into clear research questions, hypotheses, indicators, and measurement approaches.
• Design high-quality quantitative survey instruments covering areas such agricultural practices, relevance and trust of advisory, adoption of recommendations, productivity, costs, income, agency, resilience, and other farmer outcomes
• Design qualitative interview and focus group guides to explore farmers’ experiences with FarmerChat, including how and why they use it, what they find useful, barriers to engagement, and how advisory influences their decisions.
• Contribute to research design decisions, including sampling approaches, sample-size calculations, statistical power, comparison groups, and timing of measurement.
• Support experimental and quasi-experimental studies, including randomized evaluations and A/B tests, where appropriate.
• Help design and test alternative approaches to data collection, including voice-based research, AI-enabled or agentic MEL, shorter or adaptive survey formats, and different approaches to participant incentives.
• Assess the trade-offs between different methods, including validity, representativeness, bias, cost, response rates, data quality, and participant experience.

Analyze farmer and product data

• Clean, manage, and analyze quantitative data using Excel and Stata and/or R.
• Analyze FarmerChat backend and product-usage data alongside survey and qualitative data to build a richer understanding of farmer engagement and outcomes.
• Examine patterns such as frequency and intensity of FarmerChat use, types of questions farmers ask, agricultural value chains of interest, retention and drop-off, and differences across farmer segments, including gender based analysis
• Conduct descriptive and inferential statistical analysis, including significance testing, confidence intervals, hypothesis testing, and subgroup analysis.
• Link survey responses with FarmerChat usage data where appropriate to explore relationships between digital engagement, adoption of advisory, and farmer outcomes.
• Work closely with product and data colleagues to define meaningful metrics and ensure that data generated through FarmerChat can support MEL and research questions.
• Compare findings across different data-collection approaches and help determine which methods are most appropriate for different research questions.

Lead high-quality field research

• Coordinate quantitative and qualitative data collection with farmers in Kenya and Nigeria, including working with field teams, enumerators, and external research firms.
• Develop sampling plans and support recruitment of farmers for research.
• Train and support enumerators and research teams on survey instruments and research protocols.
• Monitor incoming data and conduct systematic data-quality checks throughout data collection.
• Conduct or support farmer interviews, focus groups, and other qualitative research.
• Pilot new data-collection approaches and document lessons on what works, for whom, and under what conditions.
• Ensure research is conducted ethically and that farmers’ privacy and data are appropriately protected.

Turn evidence into learning and action

• Synthesize quantitative, qualitative, and FarmerChat usage data to answer practical questions for Digital Green.
• Produce clear research briefs, presentations, reports, and other materials for internal teams, partners, and donors.
• Translate findings into practical recommendations for FarmerChat product development and program implementation.
• Work with program teams to understand whether and how FarmerChat is contributing to changes in agricultural knowledge, practices, productivity, costs, income, and other outcomes.
• Contribute evidence and analysis for donor reporting, proposals, learning agendas, and strategic decision-making.
• Document not only successful approaches but also experiments that do not work, so that learning can inform future research and product decisions.

Build strong research systems and documentation

• Maintain rigorous documentation of research designs, survey instruments, sampling decisions, datasets, codebooks, analysis files, statistical code, assumptions, and methodological decisions.
• Develop reproducible and well-organized analytical workflows, so that analyses can be reviewed, updated, and built upon over time.
• Document pilots of new MEL approaches, including methodology, implementation challenges, data-quality issues, results, and recommendations.
• Help strengthen Digital Green’s MEL systems and approaches for measuring the performance and impact of digital and AI-enabled agricultural advisory.
• Ensure that lessons from individual studies are captured and used to improve future research and measurement.

What we are looking for

Required qualifications

• Bachelor’s degree in economics, statistics, public policy, development studies, project management, agricultural economics, social sciences, or another relevant quantitative or research-oriented field, with approximately 3–5 years of relevant experience in MEL, applied research, or evaluation; or a relevant Master’s degree with approximately 1–3 years of relevant experience.
• Demonstrated experience designing quantitative surveys and other research instruments.
• Strong analytical skills, including proficiency in Excel and working proficiency in Stata and/or R or related software
• Solid understanding of applied statistics, including descriptive statistics, confidence intervals, statistical significance, and hypothesis testing.
• Understanding of sampling methods and sample-size calculations; familiarity with statistical power and power calculations.
• Experience cleaning, managing, and analyzing survey or program datasets.
• Experience conducting or supporting qualitative research, including interviews and/or focus groups.
• Strong attention to data quality and experience developing or implementing data-quality checks.
• Excellent documentation skills, including the ability to clearly document research methods, instruments, datasets, analytical decisions, and findings.
• Ability to translate data and research findings into clear insights and recommendations for colleagues who are not researchers.
• Ability to work effectively across teams, particularly with program, product, and data/technology colleagues.
• Strong written and spoken English + local language
• Demonstrated curiosity and willingness to learn new tools, analytical approaches, and research methods independently.
• Ability to travel (X days per month) in the field.

Nice to have

• Experience working in agriculture or with smallholder farmers in Kenya or East Africa.
• Experience conducting MEL or research for digital products, digital advisory services, AI-enabled tools, or other technology-for-development programs.
• Experience analyzing product or administrative data in addition to traditional survey data.
• Experience linking survey data with digital usage or transactional datasets.
• Experience with SurveyCTO, KoboToolbox, ODK, or similar digital data-collection platforms.
• Experience with randomized evaluations, A/B testing, quasi-experimental methods, and impact evaluation.
• Experience with voice-based research, conversational surveys, AI-enabled research tools, or other emerging approaches to data collection.
• Experience testing participant incentives or other approaches to improving participation and response rates.
• Experience managing external research firms, enumerators, or field research teams.
• Knowledge of Kenya’s agricultural sector and smallholder farming context.

How you work