Role: Consultant - Experimentation & A/B Testing Specialist (FarmerChat)
Location: Nairobi (Kenya- Primary location); Bangalore, India (Secondary location); Africa or Europe-based applicants will be considered
Duration:12-month contract with possibility of extension or transition to a full-time role, subject to performance and funding.
About Digital Green
Digital Green is a pioneer global not for profit organization, utilizing digital platforms and community-driven approaches to amplify the voices of smallholder farmers and improve their livelihoods. Our mission is to create a world where farmers use technology and data to build prosperous communities. By harnessing the power of technology, we facilitate knowledge sharing, capacity building, and market linkages, enabling farmers to adopt sustainable agricultural practices and increase their productivity and income.
We are dedicated to transforming the lives of under-served smallholder farmers worldwide through innovative technology solutions. Backed by leading philanthropic organizations such as the Bill & Melinda Gates Foundation (BMGF), Walmart Foundation, Rockefeller Foundation, other Private Foundations, and UK Foreign, Commonwealth & Development Office (UKFCDO), we are committed to leveraging data and technology (primarily FarmerChat) to empower smallholder farmers and strengthen agricultural extension systems.
About FarmerChat
FarmerChat is Digital Green’s AI-enabled assistant that helps smallholder farmers—especially women—access timely, trusted, and locally relevant advice on crops, livestock, and livelihoods. The platform is designed to build confidence, reduce barriers to participation, and offer actionable, locally grounded guidance in a way that feels intuitive and supportive.
We are hiring an Experimentation & A/B Testing Specialist- Consultant to help us rigorously learn what drives engagement, trust, and sustained use—particularly for women and other groups historically excluded from agricultural advisory systems. You will turn behavioral insights into structured tests, run rapid experiments across acquisition, onboarding, and early product experiences, and help shape the evidence base for what makes AI-enabled advisory truly inclusive.
What you’ll do
- Design, implement, and monitor A/B and multivariate tests across user acquisition, onboarding, content presentation, and early engagement experiences.
- Translate behavioral insights into clear hypotheses and structured experiments, working closely with product, gender research, country, and analytics teams.
- Measure experiment outcomes, interpret early behavioral signals, and produce concise recommendations that directly inform product design and messaging strategy.
- Create standardized testing methods—including templates, measurement guidelines, guardrail metrics, and decision rules—that can be used by teams across countries.
- Help establish a culture of evidence-based iteration within FarmerChat by documenting results, facilitating learning cycles, and ensuring findings inform future releases.
- Apply an inclusion lens to experimentation, examining how women, youth, low-literacy users, and farmers in low-connectivity regions experience each variant or design choice.
Here are some projects you’ll likely work on in your first 6 months:
- Define the first wave of experiments by pinpointing specific user moments—such as how new users navigate the first screens or decide to ask their first question—that need evidence to guide the next version of FarmerChat.
- Launch targeted onboarding trials to test different forms of early guidance (e.g., example questions, simplified instructions, supportive welcome messages) to see what helps women and low-confidence users get started more smoothly.
- Test approaches for collecting key profile details—like location or crop—through variations in timing and tone, evaluating which methods build trust and minimize early drop-off.
- Run comparative UI/content experiments to evaluate how different starter cards, card sequences, or supportive message styles influence clarity, confidence, and continued engagement.
- Pilot lightweight personalization tests using simple signals (location, crop type, language) to understand whether more tailored starter questions or examples improve relevance without overwhelming users.
- Turn experiment outcomes into actionable recommendations that directly influence onboarding design, content prioritization, and user communication patterns for upcoming releases.
Who You Are
You’re hypothesis-driven, curious, and motivated by understanding what truly works for diverse users. You enjoy designing clean experiments, challenging assumptions with evidence, and helping teams learn through structured, rapid testing. You are energized by the idea of making digital tools more equitable and more intuitive for farmers with varied skills, devices, and levels of digital confidence.
Qualifications
Required
- 5+ years of experience in digital experimentation, behavioral science, user research, or growth analytics.
- Bachelor’s Degree required; Master’s preferred.
- Strong grounding in experimental design, including hypothesis development, measurement planning, interpretation of effect sizes, and decision-making criteria.
- Experience running A/B or multivariate tests in mobile or web environments (e.g., Firebase, Mixpanel, Optimizely, or similar platforms).
- Ability to synthesize findings and communicate them clearly to technical and non-technical teams.
- Comfortable collaborating across product, analytics, and country teams.
- Commitment to inclusive design and interest in understanding how different user groups experience digital products.
Preferred
- Experience designing experiments in emerging-market or low-connectivity contexts, where data can be noisy or incomplete.
- Familiarity with experimentation or feature-testing platforms and best practices for guardrail metrics and sample-size planning.
- Demonstrated ability to turn behavioral questions—especially gender-related questions—into clear, testable hypotheses.
- Experience applying an equity or inclusion lens to A/B testing and product iteration.
