Farm Data Analyst
Farm data analysts analyse data from farm management platforms, sensors, and yield records to help farms make evidence-based decisions on inputs, planting timing, and resource allocation — turning increasingly available farm data into genuinely actionable insight. The role requires both agricultural domain knowledge and solid data analysis skill.
Larger commercial farms and farm-management technology platforms serving Kenyan agriculture are generating substantial operational data, but most farms currently lack dedicated analytical capacity to act on it systematically rather than through intuition alone.
- AI exposure
- 56 of 100, moderate exposure
- Hiring trend
- Growing
- Hiring rate
- 30%
- Minimum education
- Bachelor
The role
What the work is, what it pays, and what it costs you.
At a glance
- Remote friendly
- Yes
- Freelance potential
- Medium
- Freelance rate
- Ksh 3,800
- Time to senior
- 5 years
A day in the role
"A yield dip in one section of the farm could mean a dozen different things — my job is combining the data with actual field knowledge to figure out which one it really is."
What it pays
Kenyan market, per month- Entry
- KES 70,000–120,000
- Mid
- KES 130,000–220,000
- Senior
- KES 240,000–400,000
The trade offs
In its favour
- High-impact work directly improving farm profitability and resource efficiency.
- Growing demand as farm technology adoption expands.
Against it
- Many farms still lack the basic data infrastructure needed for meaningful analysis.
- Some routine detection tasks are increasingly automated by farm-tech platforms themselves.
In practice
Build a portfolio project analysing publicly available agricultural yield/weather datasets, or seek an internship with a farm technology platform or large commercial farm to gain direct practical experience.
Progression runs farm technician/data analyst → farm data analyst → head of farm analytics for a large estate or agri-tech platform, with growing scope and data sophistication.
Large commercial farms and farm management technology platforms are the primary employers, given the genuine gap between data availability and analytical capacity.
A typical day includes reviewing farm performance dashboards, investigating data anomalies, and advising farm managers on input or resource allocation decisions.
Exposure
How much of this a machine can already do, and how that was worked out.
Where this rating sits
1,516 rated careersRated above 77% of the 1,516 careers in the catalogue, which averages 43. Inside agriculture the mean is 27, across 104 careers.
What the rating is made of
Share of recorded tasks- Machine does it
- 35%Software can already complete this work end to end.
- Machine assists
- 45%A person still decides, but the drafting is done for them.
- Person does it
- 20%Judgement, relationships and accountability that do not transfer.
Named task by task
Already automated
- Detecting yield anomaly patterns
- Generating input optimisation recommendations
Still human
- Analysing farm operational data for actionable management insights
- Designing data collection processes appropriate to farm operations
- Advising farm managers on input, planting, and resource allocation decisions
- Building and maintaining farm performance dashboards
Task counts
- Tasks recorded
- 7
- Automatable now
- 3
- Still human
- 3
- Augmenting
- Yield anomaly detection,Input optimisation recommendations
- Creating
- Farm analytics platform and consulting roles
Sources
Behind the rating- FAO Digital Agriculture Resources
Getting in
The routes into the role and what each one asks for.
What to study
8 courses- Diploma in Plant Genetics Resources and BiodiversityKsh 32,000a year
- Diploma in Coffee Technology and CuppingKsh 36,320a year
- Diploma in Dairy TechnologyKsh 64,120a year
- Diploma in Cooperative ManagementKsh 67,100a year
- Artisan in General AgricultureKsh 67,189a year
- Artisan in HorticultureKsh 67,189a year
- Certificate in Agribusiness ManagementKsh 67,189a year
- Certificate in Agribusiness and EntrepreneurshipKsh 67,189a year
How people get in
Agriculture/Data Science degree + farm analytics specialisation
4 years + 6 monthsMedium cost
Standard agriculture or data science route, adding farm operations and agricultural data interpretation skills.
Data analyst transition into agriculture
6-12 monthsLow cost
Existing data analysts add agricultural domain knowledge to interpret farm data meaningfully.
Tools of the trade
Farm management platforms (FarmLogs-style)
Agri-TechRequiredPaid
Excel
AnalysisRequiredPaid
Interview preparation
2 questionsA section of a farm shows lower yields than the rest for the third season in a row. How do you investigate using available data?
SituationalMid
Look for systematic investigation: checking soil data, input application records, and weather/microclimate differences for that section before drawing conclusions.
How would you help a farm manager decide whether a data-driven input change is actually worth adopting?
TechnicalSenior
Should discuss framing recommendations in clear cost-benefit terms and, where possible, running a small-scale test before full-farm rollout.
Common misconceptions
More farm data automatically leads to better decisions.
Raw data (sensor readings, yield logs) requires genuine agricultural context and analytical rigor to turn into actionable recommendations — data volume alone doesn't guarantee useful insight.
This is the same as general business data analytics applied to farming.
Effective farm data analysis requires real agronomic and operational context (weather patterns, crop biology, seasonal cycles) that generic business analytics training doesn't provide.
What happens next
How the role changes from here, and where it leads.
The near term
Growing as farm technology platforms expand and input costs raise the value of good data
- Farm management platform adoption generating more usable operational data
- AI-assisted anomaly detection changing the analyst's role toward interpretation and recommendation
- What to do
- Build genuine agricultural domain knowledge alongside data analysis skill — the interpretation and recommendation work is what's valuable, not just running dashboards.
Where pay is heading
2024 to 2030Monthly pay in Kenyan shillings, rounded to the nearest thousand. These are projections, not observations.
Growth outlook
- Net demand change
- 22
- Over
- 2025-2028
- Drivers
- Growing farm management technology platform adoption,Rising input costs increasing ROI of data-informed decisions
- Headwinds
- Many farms still lack basic data collection infrastructure
Supply and demand
- Demand
- 34
- Supply pressure
- 32
- Balance
- Balanced
What to learn
- Farm data analysis and interpretation
- Agricultural operations context
- Farm management platform tools
Where people move next
2 recorded movesLine length under each name is the distance of the move: shorter means more of what you already do carries over. Marked lines are steps up rather than sideways.
- Precision Agriculture Specialist
Easy65% skill overlapLateral
Broader precision agriculture role beyond pure data analysis specifically.
- Data Scientist
Moderate50% skill overlapPromotion
Broadens from agriculture-specific analysis into general data science work.
Related careers
Kenyan market notes
Large commercial farms and farm-technology platforms are the primary employers, with genuine underused data creating real opportunity for analysts who can bridge agriculture and data analysis.
Further reading
This role is rated 56 out of 100 today. Save it and the app keeps that number, then tells you by how much it has moved when the record is next reviewed.