Skip to content
Nairobi · KenyaFree to read
Science

Research Scientist (R&D)

Research Scientists in R&D design and conduct experiments to advance knowledge in fields like agriculture, health, and technology. In Kenya and East Africa, they often address local challenges such as crop disease, climate resilience, and infectious diseases. As of 2026, AI tools assist with data analysis and literature review, but human creativity and domain expertise remain critical for hypothesis generation and experimental design. The role is adapting to incorporate AI-driven methods, but core scientific reasoning and ethical considerations sustain demand for skilled professionals.

AI exposure
44 of 100, moderate exposure
Hiring trend
Growing
Hiring rate
65%

The role

What the work is, what it pays, and what it costs you.

At a glance

Work environment
Labs, field stations or universities; equipment intensive and protocol driven.
Adaptation level
Moderate

A day in the role

Designing and running experiments, lab/field work, data analysis, scientific writing and collaboration with research teams and funders.

What it pays

Kenyan market, per month
Entry
1,200,000
Mid
2,500,000
Senior
4,500,000

The trade offs

In its favour

  • Frontier discovery; intellectually rich.
  • Global collaboration opportunities.

Against it

  • Grant-dependent; slow career progression.
  • Publish-or-perish pressure.

In practice

BSc + MSc + PhD. Join a research institute (KEMRI, KALRO, ILRI, ICIPE) or university; publish and win grants.

Research scientist → senior → principal investigator → programme lead / professor.

Strong research ecosystem — KEMRI, KALRO, ILRI, ICIPE and universities. International collaboration is common.

Designing experiments, field/lab work, analysing data, writing papers and grants, mentoring juniors.

Exposure

How much of this a machine can already do, and how that was worked out.

Where this rating sits

1,516 rated careers
44
lowmoderatehigh
020406080100

Rated above 56% of the 1,516 careers in the catalogue, which averages 43. Inside science the mean is 45, across 71 careers.

What the rating is made of

Share of recorded tasks
Machine does it
39%Software can already complete this work end to end.
Machine assists
28%A person still decides, but the drafting is done for them.
Person does it
33%Judgement, relationships and accountability that do not transfer.

Named task by task

Already automated

  • Literature synthesis
  • Simulation runs
  • Data analysis
  • Hypothesis generation

Still human

  • Research question framing
  • Experimental design
  • Field/lab work
  • Interpretation and publication
  • Funding and collaboration
  • Mentoring

The six things it was scored on

0 to 100 each
Digital surfaceraises exposure
80

How much of the work already happens inside software.

People and inventionlowers exposure
80

Work that needs trust, persuasion or an original idea.

Rule bound thinkingraises exposure
55

Decisions that follow a procedure rather than a judgement.

Regulatory stakeslowers exposure
55

Where a named person has to carry the liability.

Physical presencelowers exposure
40

Work that has to happen in a place, with hands.

Routine intensityraises exposure
35

How much of it repeats in the same shape each time.

Task counts

Tasks recorded
0
Automatable now
0
Still human
0
Displacing
Routine assay and literature screening,Standardised data processing
Augmenting
Hypothesis generation and literature synthesis,AlphaFold-style structural prediction,High-throughput data analysis
Creating
AI-for-science roles,Biotech and genomics roles,Research-data engineering

Sources

Behind the rating
  • Frey & Osborne (2013), 'The Future of Employment', Oxford Martin
  • McKinsey Global Institute, 'The Future of Work' (2017/2023)
  • OpenAI/UPenn, 'GPTs are GPTs' (2023), occupational LLM exposure
  • WEF, 'Future of Jobs Report' (2023)

Getting in

The routes into the role and what each one asks for.

What to study

8 courses

How people get in

  • University Degree

    4 yearsHigh cost

    BSc in the relevant science (Biology, Chemistry, Physics)

  • Master's / PhD

    2-5 yearsHigh cost

    Postgraduate study for research roles

  • Laboratory Technician

    2-3 yearsMedium cost

    Diploma + experience in research or industry labs

Certifications

  • PhD

    Universities48 months

  • Research ethics (KEMRI/SERU)

    SERUKsh 10,0001 monthsRequired

Tools of the trade

  • Python / R / MATLAB

    dataRequiredFree

  • Specialised lab/field equipment

    researchRequiredFree

  • Elicit / Consensus

    researchRequiredFree

Who hires

Common misconceptions

  • Science graduates only become teachers.

    They work in research, industry, health, energy, environment and data.

  • Pure science has no jobs in Kenya.

    Kenya's labs, manufacturing, agriculture and energy sectors hire science graduates.

  • You must go abroad to do real research.

    Kenya has growing research institutions and universities.

What happens next

How the role changes from here, and where it leads.

How the role changes

2024-2030

Expect steady augmentation rather than wholesale replacement. Practitioners who embrace AI tools will out-earn those who don't.

  1. 2024already here

    AI copilots augment daily work; productivity gains for adopters.

  2. 2027projected

    Augmentation deepens; some routine sub-tasks automated.

  3. 2030projected

    Practitioners who pair domain expertise with AI tools pull ahead.

The near term

Moderate AI change by 2028: productivity gains for adopters, with ~35% of routine work automated.

  • AI copilots become standard (~77% adoption by 2028)
  • ~35% of repetitive sub-tasks automated
  • Role shifts toward review, judgement, and orchestration
  • Scientific computing becomes a differentiator
  • Elicit / Consensus adoption reshapes daily workflows
What to do
Here, adopt the AI copilots for your field this year like Elicit / Consensus and AlphaFold / RoseTTAFold, and reposition around what AI can't do — Scientific computing, ML for science, and complex problem-solving. Net effect is productivity, not job loss, for those who adapt.

Growth outlook

Net demand change
13
Over
2024-2030
Drivers
Growing R&D and biotech,Climate and health research
Headwinds
Funding cycles

Supply and demand

Demand
65
Supply pressure
8
Balance
Balanced

What to learn

  • Scientific computing
  • ML for science
  • Research data management

Tools worth knowing

  • Elicit / Consensus

    Priority: Essential

    AI literature review

  • AlphaFold / RoseTTAFold

    Priority: Recommended

    Protein structure prediction

  • ChatGPT / Claude (Advanced Data Analysis)

    Priority: Essential

    Data analysis and coding

Kenyan market notes

Opportunities are growing across Kenya's research and science sector, with the strongest demand in KEMRI, KALRO, ILRI, universities, and biotech startups. The sector is being shaped by health and agricultural research, genomics, and climate science.

Further reading

Keep this

This role is rated 44 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.