Health Data Evaluator
Health Data Evaluator in Kenya represents an essential professional discipline powering operational capability and strategic excellence across modern organizations. Practitioners navigate evolving regulatory standards, data-driven software tools, and dynamic economic models to deliver measurable institutional results across East Africa. In the Kenyan context, practitioners must adhere to national statutory frameworks, professional codes of ethics, and industry best practices established by relevant regulatory authorities. Career advancement in Kenya typically rewards demonstrated operational reliability, enabling experienced professionals to transition into senior supervisory, quality assurance, or independent technical consulting roles across commercial and public enterprises.
The short answer
- Will AI take it
- 39 out of 100, low exposure. About 30% of the tasks still need a person.The detail
- Is anyone hiring
- Hiring is growing, with net demand +30% over 2024-2030.The detail
- What it pays
- Starts around KES 60k a month and reaches KES 280k at senior level.The detail
- How to get in
- KCSE C+ (Bachelor Degree) is the usual minimum, and 8 courses in the catalogue lead to it. About 5 years to a lead role.The detail
The role
What the work is, what it pays, and what it asks of you.
Overview
In the Kenyan context, practitioners must adhere to national statutory frameworks and industry best practices established by relevant regulatory authorities. Employers increasingly prioritize candidates who demonstrate verified technical qualifications, continuous professional development, and practical field competence. Employers increasingly prioritize candidates who demonstrate verified technical qualifications, continuous professional development, and practical problem solving competence. Structured cross-functional collaboration and ongoing professional certification ensure long-term career resilience and high operational productivity across East African markets.
Career advancement in Kenya typically rewards demonstrated operational reliability, enabling experienced professionals to transition into senior supervisory, quality assurance, or independent technical consulting roles across commercial and public enterprises. Emerging technological innovations across Kenyan industrial sectors continue to transform day to day operational workflows, elevating demand for skilled personnel who combine fundamental mastery with modern digital tool proficiencies. Practitioners frequently liaise with statutory regulatory commissions and local enterprise leadership to guarantee that all operational methodologies comply with national safety and quality mandates.
Work environment
- Work environment
- Hospitals, clinics, labs or community settings; ppe and infection control vigilance required.
- Work style
- Empathetic and rigorous; high stakes, evidence based and team oriented.
- Physical demands
- sedentary
- Travel
- Occasional
- Remote working
- Remote friendly
- Freelance potential
- Medium
A day in the role
The day begins by extracting and cleaning data from DHIS2 and mobile health survey databases, then building dashboards in Power BI to track disease outbreak patterns across districts. I run statistical models in R to identify clusters of reported malaria cases and flag anomalies for the epidemiology team. After collaborating with epidemiologists to generate weekly surveillance bulletins, I brief health department officials on findings. The afternoon ends with documenting methodology and preparing data for an upcoming vaccination coverage study. You coordinate closely with cross functional colleagues to align on immediate deliverables, double checking equipment readiness and standard operating protocols. Throughout the shift, you document system performance metrics, consult with operational supervisors on technical exceptions, and uphold rigorous occupational health and environmental safety protocols.
In the afternoon, you execute core deliverables, consult with cross functional colleagues, document operational outcomes, and ensure that all equipment and handover notes are fully updated before completing the shift. Before completing the shift, you reconcile physical logs, review operational checklists with the oncoming team, archive incident reports, and brief project supervisors on task completion.
What it pays
Kenyan market salary bands, monthly in KES- Entry level
- KES 60k – 90k
- Mid-level specialist
- KES 120k – 180k
- Senior / lead
- KES 200k – 280k
Monthly pay in Kenyan shillings, rounded to the nearest thousand. The shaded band is the distance between entry and senior pay, which is the part that is changing. These are projections, not observations.
The trade-offs
| In its favour | Against it |
|---|---|
| Your analyses directly inform disease surveillance, vaccination campaigns, and health policy, saving lives in Kenya. | Data quality issues from paper-based records in rural clinics force analysts to spend weeks cleaning messy datasets. |
| Rapidly growing field with roles at ministries, WHO, CDC, and NGOs; salaries range from KSh 100,000-300,000. | Decisions based on your work can be slow due to bureaucratic red tape, reducing the immediate sense of accomplishment. |
| Demand for data fluency ensures strong job security and options to pivot into tech or global health. | Funding often ties to specific health crises; when malaria or HIV funding shifts, jobs may disappear. |
| Opportunities for advanced training (online courses, workshops) sponsored by employers to build specialized skills. | Working with sensitive health data requires strict confidentiality, limiting social sharing about your impactful work. |
In practice
Public health data analysts apply statistical analysis and data visualization to health system data, disease surveillance, and population health research worldwide. They work with health information systems like DHIS2, epidemiological datasets, and health survey data to inform policy at ministries of health, research institutes, and international organizations like the WHO, CDC, and UNICEF. Analysts serve national and regional health departments, translating complex health data into actionable insights for resource allocation and intervention planning. The position requires expertise in R, Stata, GIS tools, and familiarity with global health information systems. Career progression leads to senior epidemiologist or health informatics director roles. The role is the same worldwide whether working locally, remotely, or on an H1B visa, as core skills and procedures are identical.
Core responsibilities include designing epidemiological study protocols and analysis plans, operational coordination, and ensuring strict adherence to Kenyan statutory frameworks and quality standards.
The public health data analyst market in Kenya is growing due to digital health initiatives and donor-funded programs. Key sectors include HIV/AIDS (e.g., PEPFAR), malaria, maternal health, and disease surveillance. Major employers include Ministry of Health, county health departments, KEMRI, CIHEB, Elizabeth Glaser Pediatric AIDS Foundation, and UN agencies like WHO and UNICEF. Job concentration is highest in Nairobi, with opportunities in Kisumu, Mombasa, and other counties.
Health Data Evaluator Specialist, Senior Health Data Evaluator, Health Data Evaluator Lead, Health Data Evaluator Consultant
Exposure
How much of this a machine can already do, and how that was determined.
Where this rating sits
3,562 rated careers| Score | Careers |
|---|---|
| 0 to 4 | 29 |
| 5 to 9 | 22 |
| 10 to 14 | 116 |
| 15 to 19 | 290 |
| 20 to 24 | 542 |
| 25 to 29 | 297 |
| 30 to 34 | 305 |
| 35 to 39 | 195 |
| 40 to 44 | 253 |
| 45 to 49 | 279 |
| 50 to 54 | 264 |
| 55 to 59 | 156 |
| 60 to 64 | 101 |
| 65 to 69 | 130 |
| 70 to 74 | 128 |
| 75 to 79 | 151 |
| 80 to 84 | 163 |
| 85 to 89 | 86 |
| 90 to 94 | 54 |
| 95 to 99 | 1 |
Rated above 50% of the 3,562 careers in the catalogue, which averages 43. Inside health sciences the mean is 31, across 318 careers.
What the rating is made of
Share of recorded tasks- Machine does it25%
- Software can already complete this work end to end.
- Machine assists45%
- A person still decides, but the drafting is done for them.
- Person does it30%
- Judgement, relationships and accountability that do not transfer.
Named task by task
Already automated
- Automated DHIS2 data extraction and indicator calculation
- AI-powered disease outbreak detection from surveillance data streams
- Automated statistical analysis and significance testing for health surveys
- Natural language generation for health report summaries
- Automated geospatial mapping of disease patterns and health facility coverage
Still human
- Designing epidemiological study protocols and analysis plans
- Interpreting health data in the context of Kenyan health policy and systems
- Engaging with county health management teams for data-driven decisions
- Conducting field data collection supervision and quality assurance
- Publishing research findings in peer-reviewed journals and policy briefs
- Ethical review and data governance for sensitive health information
| Already automated | Still human |
|---|---|
| Automated DHIS2 data extraction and indicator calculation | Designing epidemiological study protocols and analysis plans |
| AI-powered disease outbreak detection from surveillance data streams | Interpreting health data in the context of Kenyan health policy and systems |
| Automated statistical analysis and significance testing for health surveys | Engaging with county health management teams for data-driven decisions |
| Natural language generation for health report summaries | Conducting field data collection supervision and quality assurance |
| Automated geospatial mapping of disease patterns and health facility coverage | Publishing research findings in peer-reviewed journals and policy briefs |
| — | Ethical review and data governance for sensitive health information |
Your skills, sorted
16 skills recordedBeing absorbed
- Routine DHIS2 data extraction
- Standard indicator calculation
- Automated report formatting
Worth more with the tools
- Statistical analysis in R and Stata
- Disease surveillance data processing
- Geospatial analysis and mapping
- Health survey data analysis
- Data visualization for health indicators
Holding their value
- Epidemiological study design
- Health policy interpretation
- County health team engagement
- Field data collection supervision
- Research publication writing
- Ethical review and data governance
The six things it was scored on
0 to 100 each- Digital surfaceraises exposure
- 85
- Regulatory stakeslowers exposure
- 70
- Rule bound thinkingraises exposure
- 55
- Routine intensityraises exposure
- 50
- People and inventionlowers exposure
- 50
- Physical presencelowers exposure
- 30
How much of the work already happens inside software.
Where a named person has to carry the liability.
Decisions that follow a procedure rather than a judgement.
How much of it repeats in the same shape each time.
Work that needs trust, persuasion or an original idea.
Work that has to happen in a place, with hands.
Task counts
- Tasks recorded
- 10
- Automatable now
- 3
- Still human
- 3
- Displacing
- Boilerplate code generation (now AI-assisted),Routine testing and refactoring,Basic data cleaning
- Augmenting
- AI pair-programming (Copilot),Automated code review and test generation,LLM-accelerated research and analysis
- Creating
- Applied AI/ML engineering,MLOps and AI reliability,AI product and data-product roles
Sources
Behind the ratingGetting in
The routes into the role, credentials, and tools required.
What to study
8 courses- Diploma in Human BiosciencesKsh 34,920a year
- Certificate in Health Services SupportKsh 50,500a year
- Certificate in HIV/AIDS ManagementKsh 63,290a year
- Artisan in Community HealthKsh 67,189a year
- Certificate in Health Records and ITKsh 67,189a year
- Certificate in Science Laboratory TechnicianKsh 67,189a year
- Certificate in Science Laboratory TechnologyKsh 67,189a year
- Craft in School Laboratory TechnicianKsh 67,189a year
How people get in
University Degree
4 yearsHigh cost
BSc in Public Health, Statistics, or Computer Science from UoN, JKUAT, or Moi University
Bootcamp
6 monthsMedium cost
Data science bootcamp at Moringa School or Africa Data School often includes health data modules
Online Certification
12 monthsLow cost
Coursera/edX specializations in biostatistics or health informatics
Industry certifications
3 verified credentialsCertified Health Data Analyst (CHDA)
AHIMAKsh 75,0006 months
Google Data Analytics Professional Certificate
GoogleKsh 22,5006 months
Certificate in Monitoring and Evaluation
Kenya Institute of Management (KIM)Ksh 30,0003 months
Tools of the trade
8 core toolchainsWho hires
5 verified employersInterview preparation
3 curated questionsWalk me through the process of cleaning and analyzing DHIS2 data for a malaria outbreak investigation in a Kenyan county, including how you would handle missing or inconsistent records.
TechnicalMid
Emphasize data validation rules, use of R/Python for cleaning, collaboration with county health teams, and statistical methods for outbreak detection.
Describe a time you had to communicate a complex data finding to a non-technical Kenyan public health official who was skeptical about the results.
TechnicalMid
Show ability to simplify visuals, build trust through transparent methods, and relate findings to policy priorities.
You are analyzing immunization data for a county and notice a sudden drop in coverage. The health records team says it's a data entry issue, but you suspect a real supply chain problem. What do you do?
SituationalMid
Investigate both possibilities: cross-check with vaccine stock reports, interview facility staff, perform data quality audit, and present evidence to decision-makers.
Common misconceptions
Public health data analysts just count cases and make charts
They conduct outbreak investigations using epidemiological methods, analyze survey data with complex sampling weights, model disease transmission, and evaluate program effectiveness using quasi-experimental designs. An analyst might use difference-in-differences to determine whether a vaccination campaign reduced measles incidence.
The role is the same as a general data analyst
Public health data requires understanding of epidemiological study designs, confounding, selection bias, and the limitations of health data sources. An analyst who treats health data like sales data will produce findings that are statistically significant but epidemiologically meaningless.
Public health data analysis is just for government agencies
NGOs, insurance companies, hospitals, pharmaceutical companies, and global health organizations all employ public health data analysts. An analyst at a malaria NGO might use satellite data and case reports to target bed net distribution, which is operational, not just surveillance.
Professional bodies & associations
- Kenya Medical Practitioners and Dentists Council (KMPDC)
- Kenya Health Professionals Oversight Authority (KHPOA)
What happens next
How the role evolves from here, and where it leads.
How the role changes
2024-20303 tasks can already be automated today; expect substantial reshaping by 2030. Success means moving up the value chain, from executing tasks to directing AI and applying judgement.
- 2024already here
AI tools begin displacing routine tasks; practitioners adopt copilots.
- 2026already here
Significant automation of standard sub-tasks; roles consolidate.
- 2028projected
Hybrid human+AI roles dominate; pure-routine work largely automated.
- 2030projected
The data analyst in public health role is reshaped around oversight, judgement and AI-fluency.
The near term
2026-2028High disruption
High AI-driven change through 2028, 34% task automation, with the biggest impact on junior, routine work.
- Tasks automated by 2028
- 34%
- Practitioners augmented
- 81%
- Displacement risk
- 14%
- New roles created
- 28%
- ~34% of current routine tasks automated or heavily augmented by 2028
- Junior/entry work consolidates; the mid-level bar rises
- Fluency with AI clinical scribe (e.g. Nabla, DAX) becomes a hiring baseline
- Pay premium widens for AI-directing practitioners
- New 'human + AI' hybrid roles emerge in high fields
- WEF Future of Jobs Report 2025, 2025-2030 labour-market outlook (~22% structural churn)
- Stanford HAI AI Index Report 2025, enterprise AI adoption & task automation trends
- McKinsey 'The State of AI' (2024/2025), activity-level automation potential
- OpenAI/UPenn 'GPTs are GPTs' (2023) + 2024 follow-ups, occupational LLM exposure
Market outlook
- Net demand, 2024-2030
- +30%
- Demand
- 85 of 100
- Supply pressure
- 6 of 100
- Balance
- High demand
- AI adoption across every sector
- Kenya's Silicon Savannah and fintech boom
- Commoditisation of junior coding
How to stay ahead
Develop expertise in machine learning for predictive health analytics
Master data visualization tools like Power BI and Tableau for public health reporting
Strengthen knowledge of healthcare data standards (e.g., HL7, ICD-10)
Learn ethical AI frameworks for handling sensitive health data
Build domain knowledge in epidemiology and biostatistics
What to learn
- Prompt engineering
- LLM application development
- MLOps
- AI ethics & safety
- AI assisted workflow orchestration and computerized data management for Data Analyst Health
AI tools worth knowing
AI clinical scribe (e.g. Nabla, DAX)
Priority: Recommended
Automated consultation notes
UpToDate / clinical decision support
Priority: Recommended
Evidence-guided diagnosis
KenyaEMR / DHIS2 AI features
Priority: Recommended
Patient-record and reporting efficiency
OpenAI Enterprise 4
Priority: Essential
Automated technical drafting, documentation synthesis, and procedural queries for Data Analyst Health workflows
Where people move next
4 recorded moves- 01Systems AnalystSidewaysModerateexposure 801 yearpay +25%55%
- 02Research Development ManagerStep upModerateexposure 671-2 yearspay +108%50%
- 03Healthcare AdministratorStep upModerateexposure 251-2 yearspay +50%40%
- 04IoT DeveloperVery challengingexposure 752-3 yearspay +25%15%
The bar is the share of skills that carry over from this role, so a longer bar is a shorter move. Step up means the destination is more senior; sideways means it sits at the same level.
Kenyan market notes
Public health data analytics is a growing field in Kenya, supported by the country's robust health research infrastructure and devolved health system data needs. Major employers include KEMRI, KEMRI-Wellcome Trust Research Programme, the Ministry of Health, PATH Kenya, Amref Health Africa, CDC Kenya, WHO Kenya, and county health departments. KEMRI data analysts earn approximately KES 105,000-185,000 per month based on experience level. Entry-level public health data analysts earn KES 50,000-90,000 per month, mid-level analysts earn KES 100,000-180,000, and senior analysts command KES 200,000-350,000+. Research officer roles at KEMRI-Wellcome Trust offer competitive salaries with additional allowances. Qualifications typically include a BSc or MSc in Epidemiology, Biostatistics, or Public Health with proficiency in R, Stata, and DHIS2. The Kenya Medical Research Institute (KEMRI), established under the Science, Technology and Innovation Act 2013, is the primary research body.
Further reading
- Coursera, Data Science in Public Health
- edX, Data Analysis for Public Health
- DataCamp, Data Analyst with Python
- WHO, Data Management Training
- Kaggle, Public Health Datasets and Courses
- World Health Organization: Global Health Observatory Data Repository
- DHIS2: Health Information Systems in Kenya
- Kenya Ministry of Health: Health Information Systems Reports
- Gates Foundation: Data for Health and Development
- McKinsey & Company: The Future of Data Analytics in Public Health
- Kenya Medical Practitioners and Dentists Council