Digital Agronomist

Role title Digital Agronomist Department Agronomy - Digital Agriculture and Product Enablement Location Accra, Ghana, with regular travel to assigned farms, field teams, fulfilment-centre catchments and expansion territories Grade Professional / Specialist level; final internal grade and band subject to the approved job-grading framework Reports to Senior Agronomist Director; final reporting line subject to the approved organization structure Direct reports None; may coordinate interns, translators, content-production support and temporary field validators without becoming their formal line manager PRIMARY MANDATE Turn approved agronomic science into safe, localized and usable digital guidance that scales through one accountable case model, enables safe triage and prioritized, verifiable field work, and continuously improves through traceable user, field and outcome evidence. Detailed responsibilities Digital agronomy strategy, roadmap and governance Translate approved crop plans, buyer specifications, protocol roadmaps, grower risks and recurring field problems into a sequenced digital agronomy backlog with defined users, decisions, dependencies, seasonal windows, evidence needs and accountable owners. Maintain a protocol-to-digital coverage matrix by crop, variety, geography, farmer segment, channel and crop stage and identify missing, obsolete, conflicting or unapproved guidance before it reaches users. Prioritize digital agronomy work using expected farmer-risk, supply, quality, yield, loss, adoption and scale impact rather than novelty, stakeholder seniority or content-production convenience. Define the source protocol, subject-matter approver, effective date, review date, applicable conditions, exclusions and rollback path for every controlled digital advisory object. Escalate conflicts between agronomic evidence, buyer requirements, product constraints, field capacity and commercial urgency to the correct decision owner without weakening technical controls. Protocol translation and digital decision logic Decompose approved crop protocols into stage-based actions, triggers, timing windows, critical limits, decision rules, required inputs, evidence requirements, exceptions and escalation thresholds that Product and Technology can implement unambiguously. Design decision trees and rule tables for crop planning, land and soil readiness, planting, nutrition, irrigation, crop protection, field observations, harvest readiness and post-harvest handling within the approved protocol scope. State assumptions, confidence, applicable crop and location conditions and remote-advice limitations and prevent a generic recommendation from being applied where field diagnosis, laboratory evidence or technical approval is required. Specify how missing, late, contradictory or low-confidence data changes the recommendation and design safe defaults that escalates uncertainty instead of presenting false precision. Maintain traceability from each digital rule, message and task to its source protocol, approval and release version and withdraw superseded content from every channel and cache. Advisory content and omni-channel experience Write clear, concise and actionable agronomy guidance for CF Grower, agent tools, SMS, USSD, IVR/voice and WhatsApp, adapting length, sequence and interaction without changing the approved agronomic meaning. Structure every priority advisory around the required action, reason, timing, method, safety precaution, evidence of completion and escalation route rather than publishing technical information without an operational decision. Develop crop calendars, checklists, visual aids, voice scripts, FAQs, prompts, reminders and follow-up questions appropriate to farmer literacy, language, disability, device and connectivity constraints. Coordinate translation and back-translation with qualified reviewers and field-test localized terms, measurements, input names and instructions before release; preserve a controlled master version. Test comprehension and usability with representative growers and field users and distinguish content, product, protocol, incentive, affordability, access and field-service barriers before recommending a change. Diagnosis, safe triage and accountable case management Define agronomic issue categories, severity, urgency, confidence, evidence requirements, remote-resolution limits, field-visit triggers and referral paths for one accountable case model. Design structured questions and evidence capture for symptoms, crop stage, distribution, timing, practices, inputs, weather, location, images and prior actions while avoiding premature diagnosis from a single signal. Review or support cases within the approved service model, provide only advice permitted by the protocol and competence boundary, and elevate severe, unusual, regulated, food-safety or low-confidence cases for physical assessment. Ensure each case has one owner, due time, current status, advice issued, field action, verification evidence, resolution code and reopening path and prevent channel handoffs from creating duplicate or abandoned cases. Analyze recurring case themes, unsafe advice, reopenings, field delays and unresolved causes and convert systemic gaps into protocol, product, training, research or operational improvement actions. Weather, pest, disease and agronomic risk intelligence Define agronomic use cases and action thresholds for approved weather, crop, pest, disease, soil, satellite, field-observation and outbreak signals in partnership with Research, Field Agronomy, Product and Data. Validate the relevance, timeliness, geographic resolution, confidence, false-positive risk and farmer actionability of a signal before using it to trigger an advisory or field task. Create targeted alerts that state the affected cohort, observation or risk, approved preventive or response action, timing, uncertainty and escalation route and avoid presenting a forecast as a confirmed diagnosis. Monitor acknowledgements, field verification, actions, false alarms, missed events and outcomes and tune approved rules through controlled change rather than informal message edits. Escalate suspected outbreaks, prohibited input use, food-safety risk, material crop loss or emerging threats through approved incident and technical-governance channels. Product discovery, specification, testing and release Join discovery for grower, agent, field-service and agronomy workflows; provide the agronomic problem, user decision, source protocol, risk, assumptions, edge cases and measurable outcome rather than prescribing a software solution alone. Write agronomic requirements, content models, decision tables, data fields, validation rules, error states, offline behaviour, alerts, permissions, audit requirements and acceptance criteria for relevant features. Create realistic test scenarios covering crop stages, geographies, languages, channels, missing and conflicting data, boundary values, severe cases, obsolete protocols, poor connectivity and unauthorized users. Perform agronomic acceptance testing, document defects and residual risks, verify fixes and provide objective sign-off evidence while Product retains product acceptance and Technology remains accountable for implementation quality. Monitor releases for advisory errors, broken rules, delivery failure, unsafe edge cases and field impact and recommend pause, withdrawal, correction or rollback when risk exceeds the approved tolerance. Data, measurement and continuous improvement Define agronomic events, fields, units, taxonomies, outcome codes and minimum evidence needed to measure receipt, comprehension, action, field verification, case closure and crop outcome consistently. Work with Data and Product to establish dashboards and cohort analyses while retaining the boundary that Data owns enterprise pipelines and models and business owners approve metric meaning. Audit content, case and field data for completeness, timeliness, duplicates, inconsistent units, impossible values, selection bias and evidence gaps and route source-system corrections to the accountable owner. Link advisory exposure and action to field-verified outcomes using an approved baseline or comparison and disclose confounding, missingness and uncertainty rather than claiming causation from correlation. Run controlled content, timing or workflow experiments only within approved agronomic and ethical boundaries; document the hypothesis, guardrails, population, success criteria, result and scale or stop decision. Maintain a learning backlog that converts usage, case, field, research and quality evidence into prioritized content, protocol, product, training and service improvements and tracks decisions to closure. Knowledge, capability, controls and collaboration Maintain a governed digital agronomy library containing current protocols, content objects, rule sets, translations, media, FAQs, test packs, approvals, releases, retirements and evidence links with role-based access and version control. Train and calibrate Field Agronomists, Agronomic Agents, customer-support users and relevant Product and QA colleagues on approved digital guidance, remote-advice limits, issue triage, evidence capture and escalation. Protect grower privacy, consent, location, farm, image and production data and comply with approved input stewardship, food-safety, environmental, intellectual-property and conflict-of-interest controls. Remain independent of input-provider incentives and do not publish unsupported claims, prescribe prohibited or unapproved treatments, change controlled protocols, promise yield or buyer acceptance, or conceal material uncertainty or incidents. Stop or immediately recommend suppression of advice that is unsafe, materially incorrect, obsolete or outside approved scope and document the risk, affected users, containment, correction and learning action. Model Complete Farmer's leadership standards of Clarity, Ownership and People-First leadership and reinforce trust, excellence, continuous learning, integrity, accountability, customer love and smart efficiency. Required experience, qualifications and technical capabilities Required experience Three to five years of relevant experience in agronomy, crop production, agricultural extension, digital agriculture, precision agriculture or agritech product delivery, including direct work with farmers or field teams. Demonstrated ability to translate crop protocols and field knowledge into stage-based recommendations, decision trees, digital content, data fields, workflows, test scenarios or remote-advisory processes. Practical crop-production experience covering crop establishment, nutrition, water, pest and disease observation, crop protection, harvest readiness, quality and post-harvest risk across at least one material crop portfolio. Experience working with digital products, mobile applications, field-service tools or omni-channel services such as SMS, USSD, IVR/voice and WhatsApp, including low-literacy and low-connectivity user conditions. Experience handling farmer questions or crop issues through structured triage and knowing when remote advice is insufficient and physical, laboratory or senior technical escalation is required. Evidence of using user, field or agronomic data to improve advice, workflow adoption, case resolution or crop outcomes without overstating causality or selectively reporting favorable results. Experience collaborating with Product, Engineering, Data, Research, Field Operations, Quality Assurance and commercial teams while protecting technical standards and approval boundaries. Demonstrated integrity in resisting unsafe shortcuts, input-provider bias, unsupported performance claims, concealed incidents and pressure to release advice without adequate evidence or approval. Qualifications Bachelor's degree in Agronomy, Crop Science, Plant Science, Horticulture, Soil Science, Plant Pathology, Agricultural Extension, Agricultural Engineering or a closely related discipline; a relevant master's degree is advantageous. Strong working knowledge of Good Agricultural Practices, integrated crop and pest management, input stewardship, crop-stage decision making, food-safety and environmental controls relevant to the assigned crop portfolio. Digital product or service-design training, content design, data analysis, GIS, remote sensing, weather analytics, instructional design or human-centred design is advantageous. Strong numerical and data discipline, including units, rates, thresholds, crop calendars, validation rules, basic descriptive analysis, spreadsheet use and interpretation of field and platform performance data. Excellent plain-language writing and verbal communication and the ability to preserve technical meaning across short text, voice, visual and field instructions for users with different literacy and technical backgrounds. Fluent professional English; relevant Ghanaian language capability is required or advantageous by territory, and French is advantageous for cross-border work. Readiness for regular field travel and crop-cycle work is essential. #J-18808-Ljbffr Complete Farmer LTD