Statistician
38AI EXPOSURE TODAY38
20-YEAR SCENARIO
NOT A FORECAST83%
NOT A FORECAST83%
THE DOOR · ENTRY DIFFICULTY TODAYB
STARTING PAY£25,000 - £35,000
NO MOATNo physical, legal or personal barrier protects this work from software.
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CAREERMASH (EN)FROM MATHEMATICAL SCIENCES →
Statistician
Statisticians are experts at making sense of numbers. They collect data, find the patterns hidden in it, and use what they find to help people make good decisions - everything from how the NHS plans hospital beds to which advert a company should run.
THE DOOR: ENTRY DIFFICULTY TODAY, graded A (easy) to E (extremely hard). A Careermash rule-of-thumb index built from our AI exposure index and the job's moat class. It is not a forecast and not a count of job openings.
AI EXPOSURE TODAY is a Careermash index from 0 to 100 of how exposed this job's everyday tasks are to AI today. We estimate it by matching published research on how people use AI to this job, usually by keyword or subject area, and we lower it where the work is protected (for example by physical, personal or legal requirements). It is not a direct measurement of how much people in this job use AI.
AI helps here, but has not taken over
AI exposure for this job is below 50 on our index, and the day-to-day work still leans on a person to decide, check and take responsibility. Nothing formally protects this job though, so the safest move is to keep building the judgement AI cannot yet copy.
The role
As a statistician, you turn piles of numbers into clear answers. Businesses, hospitals, sports teams and the government all collect huge amounts of data, and they need someone who can work out what it actually means. That is your job.
Most days you will design ways to gather data - like surveys or experiments - then use maths and computer software to study it. You look for patterns, work out how sure you can be about them, and explain what you have found so anyone can understand it. You will use software like R or Python, and you need solid maths skills. But the most important part is your ability to ask the right questions and communicate what the numbers tell you in plain English, because the people using your findings might not be mathematicians.
Daily responsibilities
- Collect and clean data from various sources to ensure accuracy and reliability.
- Design experiments and surveys to gather relevant information for analysis.
- Utilize statistical software to perform complex analyses and interpret results.
- Communicate findings through detailed reports and presentations to stakeholders.
- Collaborate with cross-functional teams to integrate statistical methods into projects.
- Stay updated on the latest statistical techniques and trends to enhance methodologies.
- Develop predictive models to forecast trends and inform strategic planning.
Does a degree help here?
A UK degree in Mathematical Sciences not only provides a solid foundation in statistical theory but also equips graduates with practical skills highly valued by employers. UK universities are renowned for their rigorous academic standards and industry connections, giving graduates a competitive edge in the job market.