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Biostatistician

Statistical data scientists collect mountains of numbers and work out what they mean. They spot patterns that help companies make better decisions, from how to sell more products to how to run things more efficiently.

Biostatistician

38

Mathematical Sciences

AI IMPACT
AI CAN DO38%moving to83%
THE DOOR, NOWB
THE DOOR, 20 YRSD
STARTING PAY£30,000 - £36,000
NO MOATNo physical, legal or personal barrier protects this work from software.
AI helps here, but has not taken over
AI can already do some of this job, but 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 statistical data scientist, you gather data from many different places and clean it up so it's ready to use. You then build computer models to look for hidden patterns - like spotting which customers might buy a product, or when a machine might break down. You explain what you've found through charts and graphs so people can understand it.

You work with teams across the business who ask you questions like 'should we open a shop here?' or 'how can we make this faster?' You help them think about what data they need and what the numbers actually tell them. The job means learning new tools regularly and staying curious about what the data shows.

Daily responsibilities

  • Collect and clean large datasets from various sources to ensure data integrity and usability.
  • Develop and implement statistical models and algorithms to analyze trends and patterns.
  • Visualize data findings through charts and dashboards to communicate insights effectively.
  • Collaborate with cross-functional teams to understand business needs and provide data-driven recommendations.
  • Conduct hypothesis testing and predictive analytics to inform strategic decisions.
  • Stay updated with the latest statistical methodologies and tools to enhance analytical capabilities.
  • Document and present findings to stakeholders, translating complex statistical concepts into understandable terms.

Does a degree help here?

A UK degree in Biological Sciences or a related field equips candidates with a robust understanding of both statistical methods and biological principles, making them highly sought after in the UK job market. The emphasis on research and practical experience in UK universities prepares graduates to tackle real-world challenges effectively.

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AI EXPOSURE = the share of a job's day-to-day tasks AI can already do today, from the same exposure engine used across this site (Anthropic labour market research, 2026, observed real-world AI usage by occupation). Higher means more exposed. It is a measurement of now, not a prediction. THE DOOR = how hard the job is to get into, grade A (easy) to E (extremely hard), from each career's published forecast (OpenAI, "The AI Jobs Transition Framework", Richmond 2026, CC BY 4.0). A card marked MOAT NOT YET CLASSIFIED has a real exposure score but no entry yet in our moat register, so we make no claim about what structurally protects it. Scorecard grades and verdicts are Careermash editorial judgment: we show forecasts as forecasts and own our conclusions. Salary and pathway figures are each career's own published profile. Careermash is a service provided by What School Ltd.

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