Data scientist
Find patterns in raw data to help solve problems or make predictions.
About the job
Career insights – Data scientist
What it's like
Businesses use data analytics to improve decision making. It’s how organisations get a better understanding of their customers or work out product trends.
For example, think about flight prices. Airlines put prices up during busy times when lots of people want to fly. During quieter times, they lower them to attract customers. Data science helps inform these decisions.
You’d collect and analyse large amounts of raw data from a range of sources like surveys, analytics or cookies on a website. Then you’d look for patterns or insights using different methods. For example, algorithms, data mining, artificial intelligence, machine learning and statistical tools.
You’d then present your results to help make predictions or find solutions to problems.
Things you might do
identify issues or opportunities to use data in an organisation
collect raw data and turn it to a useable format
look for patterns in the data to help identify trends
test data mining models to select one that suits the need
solve business related problems using machine learning tools and statistical techniques
present your results to your organisation or client
stay on top of analytic techniques like machine learning and text analytics
work with a variety of programming languages, including 'SAS', 'R' and 'Python'
You could work in a variety of industries. Depending on your interests and the opportunities available, you could work in:
finance
fintech (financial technology)
academia
scientific research
health
retail
information technology
government
ecommerce
"Data science was seen as nerdy but now it's creative. Communication matters because you have to sell what you uncover and that means telling stories around data. The future belongs to people with soft skills just as much as to those who master hard data analysis."
Euan Davis
Data Scientist, Cognizant
Hours
Environment
Travel
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Engineering and manufacturing Construction and built environment Life sciences Financial and professional services Digital technologies Creative Chemical sciences
Top skills
Skills are things you're good at. Whether you know what yours are or not, everyone has them!
It's useful to learn which ones are important in a job so you know the areas you need to brush up on. It can also help you work out if you're suited to a career.
Top specialised skills
These are the top specialised skills that have been found in job vacancies across Scotland. From March 2024 to March 2025.
- data science
- machine learning
- exploratory data analysis
- valuation models
- universal testing machines
- linear model
- factor analysis
- probability distribution
- cognitive computing
- biosensors
Meta skills
Here are some of the meta skills you'll need to do this job.
- analysing
- making decisions
- developing a plan
- attention to detail
- researching
- problem solving
- creative
- written communication
- verbal communication
- cooperating
Your skills are important
Our unique skillsets are what make us stand out from the crowd. Learn about each skill in depth and discover what employers look for in your applications and interviews.
Getting in
Explore each section to find more information about getting into this career.
Colleges and universities will list subjects you'll need for entry to a course. Some useful subjects include:
Computing Science
Maths (Mathematics)
Foundation Apprenticeship: Hardware and Systems Support
Applications of Mathematics
You can get a head start in this career by doing a Foundation Apprenticeship in S5 and S6.
You'll get an SCQF level 6 qualification which is the same level as a Higher. You'll also learn new skills and gain valuable experience in a work environment.
Discover what's on offer at your school on Apprenticeships.scot.
Entry requirements for courses can change. Always contact the college, university or training provider to check exactly what you’ll need.
To become a data scientist, you'll usually need a degree in a computer science, mathematical or science-based subject. The following degree subjects may be particularly useful:
computer science
statistical data science
data science
mathematics and operational research
statistics
maths
You'll also need experience of computer programming and strong coding skills. An understanding of data collection and pattern recognition is also important.
Qualifications are available at postgraduate level. If you don’t have a related degree, you could take a postgraduate qualification in a relevant subject area. For example, in big data, business analytics or data science.
Not all employers list specific qualifications you need. They do ask for relevant experience that demonstrates a range of transferable skills. This is usually work based.
It's also helpful to have experience in the use of the programming language 'Python'. Experience with database interrogation and analysis tools, such as 'Hadoop', 'SQL' and 'SAS' would also be useful.
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