Technology & Data

Data Scientist

Builds statistical models and machine learning systems to find patterns or make predictions.

Content last reviewed: August 2026

A data scientist's day typically mixes exploratory analysis (digging through data to understand it and form hypotheses), model-building (using statistics or machine learning to predict something or find patterns), and communicating results. Much of the actual time goes to preparing and cleaning data, model-building itself is often a smaller share of the work than people expect.

Collaboration with engineers (to get a model into production) and with business stakeholders (to make sure the model answers a real, well-defined question) is a constant part of the role, not a side task.

Core tasks

✓Exploring and cleaning datasets
✓Building and testing statistical or machine learning models
✓Evaluating model performance and limitations
✓Collaborating with engineers to deploy models into products
✓Communicating findings and their uncertainty to stakeholders
✓Designing experiments (like A/B tests) to test hypotheses

Tools & skills used

Python or RSQLStatistics and probabilityMachine learning libraries and frameworksData visualizationExperimental design

Typical entry paths

→Statistics, Data Science, or Applied Mathematics are the most direct routes
→Computer Science with a statistics/ML focus
→Graduate degrees are common in this field, though not always required
→Fields like Economics, Physics, or Biology with strong quantitative and programming skills

Common misconceptions

Most of the job isn't building flashy machine learning models, it's data cleaning, exploration, and communicating uncertainty honestly.
A model that performs well on paper isn't automatically useful; understanding the business context matters as much as the technical model.
It's not the same job as a data analyst or ML engineer, though the boundaries vary a lot by company.

Frequently asked questions

What does a Data Scientist do?

Builds statistical models and machine learning systems to find patterns or make predictions.

What are the core tasks of a Data Scientist?

Day to day, this typically includes: Exploring and cleaning datasets; Building and testing statistical or machine learning models; Evaluating model performance and limitations.

What tools or skills does a Data Scientist use?

Common tools and skills for this role include Python or R, SQL, Statistics and probability, Machine learning libraries and frameworks.

How do people typically become a Data Scientist?

Statistics, Data Science, or Applied Mathematics are the most direct routes. Computer Science with a statistics/ML focus.

What's a common misconception about being a Data Scientist?

Most of the job isn't building flashy machine learning models, it's data cleaning, exploration, and communicating uncertainty honestly.

What college majors lead to becoming a Data Scientist?

Majors that commonly lead here include Statistics & Data Analytics, Data Science, Mathematics. A major shapes what you study, it isn't a guarantee of landing this specific role.

From our guides

Computer Science vs. Data Science vs. Information Technology: What's Actually DifferentThese three majors get lumped together on nearly every college website. Here's what actually separates them in practice, and how to tell which one fits how you think.Data Analyst vs. Data Scientist vs. Business Analyst: What's the DifferenceThree job titles that show up in nearly identical postings but mean different things day to day. Here's what actually separates the work, and which majors tend to lead where.

This describes what the role typically involves day to day. It's not a guarantee of hiring, salary, or advancement, actual responsibilities vary by employer, industry, and location. See our disclaimer.