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Data Scientist

Data scientists use statistics, mathematics, programming and data analysis to find patterns, build models and help organisations make better decisions.

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Career fit

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Entry level
£32,000 (starter)
Mid-career (typical)
£32k – £83k
Senior / lead
£83,000 (experienced)
What you'll do

A day in the life

  • Clean and explore large datasets
  • Build and test statistical or machine-learning models
  • Write code in Python, R or SQL
  • Explain findings to non-technical colleagues
  • Monitor models once they are in use
The path

Your career roadmap

Every milestone from school to senior. Track progress as you complete each stage.

  1. 1

    GCSEs / school qualifications

    education
    Usually 2 years; resit routes vary

    Build foundations in maths, English and science, with computing useful preparation for later data study.

  2. 2

    A levels / equivalent

    education
    Usually 2 years; Access courses often 1 year

    Study Level 3 qualifications, often including maths, to prepare for a quantitative university degree.

  3. 3

    Relevant degree

    qualification
    Usually 3–4 years; a master's often adds 1 year

    Study statistics, programming and mathematical modelling through a quantitative degree, or an appropriate postgraduate conversion course if already a graduate.

  4. 4

    Data / project experience

    experience
    Several weeks to a year, often alongside study

    Apply data cleaning, statistical analysis and modelling to realistic problems, often alongside your degree.

  5. 5

    Junior / graduate data role

    role
    Often 1–3 years before broader responsibility

    Join a data team to analyse datasets, write queries and support modelling under guidance from experienced colleagues.

  6. 6

    Data Scientist

    role
    Often several years; progression varies

    Develop and evaluate models, design analyses and work with colleagues to turn results into decisions or usable products.

  7. 7

    Senior Data Scientist

    role
    Usually several years; no fixed timetable

    Lead complex data science projects, mentor colleagues and guide modelling choices, evaluation standards and stakeholder communication.

  8. 8

    Principal / specialist role

    role
    Ongoing; progression varies by employer

    Set technical direction across teams or provide deep expertise in areas such as causal inference, forecasting or machine learning.

What you need

Skills you'll build

Qualifications
  • Mathematics
  • Statistics
  • Data Science
  • Computer Science
  • Operational Research
  • Physics
  • Engineering
  • Psychology
  • Postgraduate conversion course (for other degree subjects)
Certifications
  • Microsoft Azure Data Scientist Associate
  • AWS Machine Learning Specialty

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