Career outlook for data scientist
Figures and forecasts for roles at the same level, which require similar skills and qualifications.
Average UK salary
£52,000
Currently employed in Scotland
3,000
Five year job forecast
+4.96%
"LMI for All" supplies our salary and employment status information. "Oxford Economics" supplies job forecasts and employment figures.
What's it like?
Businesses are increasingly using data analytics to improve decision making. It’s how an organisation gets a better understanding of their customers or identifies product trends. Think about flight prices: airlines will raise prices during busy times when lots of people want to fly to a destination and then reduce them during quieter times to attract customers. Data science helps inform these decisions.
As a data scientist you’d collect, extract and analyse large amounts of raw data from a range of sources like surveys, analytics or cookies on a website. Then, using algorithms, data mining, artificial intelligence, machine learning and statistical tools you’d look for patterns or insights. You’d will then present your results to help the business make predictions or find solutions to problems.
Things you might do
- Work with your organisation to identify issues or opportunities to use data
- Collect raw data and turn it to a useable format
- Looking for patterns in the data to help Identify trends
- Test data mining models in order to select the model that best fits the requirement
- 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
Working conditions
Hours
Environment
Travel
UK employment status
Full-time
60%
Part-time
27%
Self employed
13%
Top skills
Here are some of the skills needed for this job. Sign in to see how your skills match up.
- Cooperating
- Verbal communication
- Written communication
- Creative
- Problem solving
- Researching
- Attention to detail
- Developing a plan
- Making decisions
- Analysing
Build your skills
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Entry requirements for courses can change. Always contact the college, university or training provider to check exactly what you’ll need.
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 be expected to have experience of computer programming as well as having strong coding skills and an understanding of data collection and pattern recognition.
Qualifications are also available at postgraduate level and if you don’t have a related degree, you could take a postgraduate qualification in a relevant subject area such as Big Data, Business Analytics or Data Science.
Useful subjects
Many colleges and universities will have subjects that you must have for entry. In addition, they may also highlight additional subjects that they would value. See individual institutions websites for specific entry information.
Useful subjects would be:
- Maths
- Computer science
- Statistics
Helpful to have
While not all employers list specific qualification requirements they do ask for relevant (usually work based) experience that demonstrates a range of transferable skills.
In addition, it is helpful to have experience in the use of Python as well as database interrogation and analysis tools, such as Hadoop, SQL and SAS.
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