Data Scientist

What is a Data Scientist?

A data scientist turns messy data into decisions someone can act on. That might mean designing an experiment to test whether a change actually helped, digging into why a number moved, or building a model to estimate something the business cares about. A large part of the job is communication: an analysis nobody understands or trusts changes nothing.

• Experiments and A/B tests
• Statistical models and forecasts
• Deep-dive analyses of product behaviour
• Metrics and definitions a company relies on
• Reports and visualisations for decision makers

A high-level preview of the areas this journey covers. Your detailed roadmap comes next.

1. 1Programming fundamentals
2. 2Python
3. 3Statistics and probability
4. 4SQL
5. 5Data cleaning and exploration
6. 6Data visualisation
7. 7Experiment design
8. 8Machine learning basics
9. 9Communicating results clearly

• You are curious about why things happen
• You like statistics and careful reasoning
• You can explain a complex finding simply
• You are sceptical of results that look too good
• You want influence over decisions, not just code

Worth knowing before you commit. Every path has these.

• Real data is messy, incomplete and often wrong
• Correlation constantly looks like causation
• Stakeholders may want the answer they already believe
• The role means very different things at different companies
• Strong statistics knowledge is expected, not optional