Data scientist
Career outlook for data scientist
UK Salary Ranges
Entry-level
£32,000
£32,000
Experienced
£82,500
£82,500
Currently employed in Scotland
5,500
Salary information is provided by the "National Careers Service". "Oxford Economics" supplies job forecasts and employment figures. Due to COVID-19 the jobs market is constantly changing. Some of the information may not reflect the current situation.
What's it 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
Working conditions
Hours
Environment
Travel
UK employment status
Full-time
87%
Part-time
8%
Self employed
5%
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Find a jobTop skills
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- Cooperating
- Verbal communication
- Written communication
- Creative
- Problem solving
- Researching
- Attention to detail
- Developing a plan
- Making decisions
- Analysing
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Foundation Apprenticeships
Choosing a Foundation Apprenticeship as one of your subjects in S5 and S6 can help you get a head start with this type of job.
You'll get an SCQF level 6 qualification (the same level as a Higher) plus valuable work placement experience and skills you can't learn in a classroom.
Interested? Find out what's on offer at your school on Apprenticeships.scot.
Qualifications
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.
Useful subjects
Many colleges and universities list subjects that you need for entry. They might also highlight more subjects that they'd value. See individual institutions websites for specific entry information.
Useful subjects would be:
- maths
- computer science
- statistics
Helpful to have
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.