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Healthcare Rising

Medical Imaging AI Specialist

Build and check AI that helps doctors spot problems on scans

💡 Why it matters: Doctors read thousands of X-rays, CT and MRI scans, and AI can help point out what needs a closer look. These tools must be tested carefully and checked on many kinds of patients, because mistakes can harm people.

🌍 Around the world

💰 What it can pay

🇳🇬 Nigeria

Starting out
₦2M – ₦5M
Mid-career
₦6M – ₦15M
Senior
₦15M – ₦35M

≈ ₦500k – ₦1.3M a month mid-career. Indicative estimate by Incusim.

🇬🇧 United Kingdom

£32k – £83k

Closest National Careers Service profile: Data scientist. Typical starter to experienced salary. National Careers Service, 2026

🇺🇸 United States

$120.2k typical
Range $67.2k – $199.1k

Closest US category: Data scientists. Median pay; low and high are the 10th and 90th percentiles.. US Bureau of Labor Statistics, May 2025

🇨🇦 Canada

CA$96k typical
Range CA$62.4k – CA$145.1k

Closest Job Bank occupation: Data scientist. Hourly wage low, median and high x 2,080 hours. Job Bank (Government of Canada), 2023-2024

Yearly pay before tax. UK, US and Canada figures come from the official sources named on each card. Nigeria has no official salary survey, so those are our indicative estimates. Real pay depends on the employer, the place, your skills and experience.

🛠️ What you actually do

⚡ Skills you'll need

Get ready at school

🇳🇬 Nigeria

Subjects to be good at
MathematicsFurther MathematicsPhysicsComputer StudiesEnglish Language
Qualifications
BSc in Computer Science, Biomedical or Electrical Engineering, Medical Physics, Statistics or Mathematics (UTME, the JAMB entrance exam, usually needs English, Mathematics, Physics and one more science; check each school)Master's degree in AI, data science or medical imaging, online or abroad
Other ways in
  • Open medical imaging datasets and online AI courses for a project portfolio
  • Starting as a data analyst, software engineer or radiography professional who learns to code

🇬🇧 United Kingdom

Subjects to be good at
Maths (GCSE and A-level)Biology (A-level)Computer Science (GCSE and A-level)Physics or Further Maths (A-level)
Qualifications
Degree in computer science, maths, physics, biomedical engineering or health data science (applied for through UCAS, the university application service)Master's degree in AI, data science or medical imaging (common for this job)
Other ways in
  • Digital or data degree apprenticeships (study while you work)
  • Starting as a radiographer or healthcare scientist, then retraining in AI and data

🇺🇸 United States

Subjects to be good at
Math through calculusComputer science (AP, or Advanced Placement, Computer Science A)AP StatisticsAP Biology or Physics
Qualifications
Bachelor's degree in computer science, biomedical engineering, math or statisticsMaster's degree in AI, data science or medical imaging (common for this job)
Other ways in
  • Hospital or university research internships
  • Starting as a software developer or data analyst at a health technology company

🇨🇦 Canada

Subjects to be good at
Grade 12 EnglishGrade 12 Math (requirements vary by province)Computer science or IT courses where your school offers themPhysics (asked for by some programs)
Qualifications
University bachelor's degree in computer science, biomedical engineering, math or physicsMaster's degree in AI, data science or medical imaging (common for this job)
Other ways in
  • Co-op programs that alternate study terms with paid work terms
  • Starting as a software developer or data analyst at a health technology company

🗺️ Your path to this career

  1. 1Get strong at maths and biology, and learn Python
  2. 2Try small projects such as sorting pictures with free AI tools
  3. 3Study computer science, maths, biomedical engineering or physics
  4. 4Practise on open sets of scans and take a research or hospital placement
  5. 5Join a health technology or hospital team as a junior, then learn the safety rules for medical software

⏰ A day in the life

A hospital wants to try an AI tool that flags possible lung problems on chest X-rays. You test it on scans from older machines and find it misses more cases there. You write up the gap, show the radiologists, and work with the team on a fix.

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