How it works
The data scientist is the professional who works with data and models to generate insights and predictions. They collect, clean and analyze data, choose algorithms, train machine learning models and evaluate whether they perform well on new data.
The work involves statistics, programming, mainly Python, and business knowledge. A data scientist does not just train models: they define metrics, detect bias in the data, validate hypotheses and communicate results to non-technical people.
Practical example
A store wants to predict which customers will cancel their subscription. The data scientist brings together purchase history, support interactions and product usage, trains a classification model and evaluates accuracy on test data. If the model is good, they hand it over to the product team, which uses the forecast to offer discounts to at-risk customers.
What it's for
This role exists to turn raw data into decisions. On AI teams, the data scientist focuses more on research and models, while the AI engineer focuses on putting the model into production. Many companies combine the two roles on small teams, but specialization tends to grow as the product matures.