Data Scientists
SOC code 15-2051 · O*NET-SOC 15-2051.00 · Considerable preparation needed · Computer and IT
Bright Outlook — O*NET expects rapid growth for this occupation
Data Scientists pay
U.S. national figures, May 2025 BLS survey · How we got this number
Median pay
$120,230
a year
Hourly
$57.80
per hour
The solid band is the middle 50% of workers; the bar spans the 10th to 90th percentile.
Average pay
$126,800
$60.96 per hour
Middle 50%
$85,660 – $158,880
25th to 75th percentile
Full spread
$67,240 – $199,130
10th to 90th percentile
People employed
262,440
nationwide
National U.S. figure, May 2025. Local pay can be higher or lower.
- 10th percentile
- $67,240
- $32.33/hr
- 25th percentile
- $85,660
- $41.18/hr
- Median percentile
- $120,230
- $57.80/hr
- 75th percentile
- $158,880
- $76.39/hr
- 90th percentile
- $199,130
- $95.74/hr
Job outlook · federal projection 2024–34
+34%
Growing much faster than average
245,900
jobs in 2024
328,300
projected for 2034
About 82,400 more jobs
U.S. Bureau of Labor Statistics employment projections, 2024–34. Projections describe the broader occupation group and are estimates, not guarantees.
What does a data scientist do?
Develop and implement a set of techniques or analytics applications to transform raw data into meaningful information using data-oriented programming languages and visualization software. Apply data mining, data modeling, natural language processing, and machine learning to extract and analyze information from large structured and unstructured datasets. Visualize, interpret, and report data findings. May create dynamic data reports.
The tasks that matter most day to day
- Analyze, manipulate, or process large sets of data using statistical software.
- Create graphs, charts, or other visualizations to convey the results of data analysis using specialized software.
- Test, validate, and reformulate models to ensure accurate prediction of outcomes of interest.
- Deliver oral or written presentations of the results of mathematical modeling and data analysis to management or other end users.
- Recommend data-driven solutions to key stakeholders.
- Identify business problems or management objectives that can be addressed through data analysis.
- Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.
- Clean and manipulate raw data using statistical software.
How to become a data scientist
Preparation level: zone 4 — Considerable preparation needed
- Education
- Most of these occupations require a four-year bachelor's degree, but some do not.
- Experience
- A considerable amount of work-related skill, knowledge, or experience is needed for these occupations. For example, an accountant must complete four years of college and work for several years in accounting to be considered qualified.
- Training
- Employees in these occupations usually need several years of work-related experience, on-the-job training, and/or vocational training.
The federal survey did not capture education levels for this specific occupation, so the preparation-level card above is the best guide to the entry route.
Common questions
How much does a data scientist earn?
The national median is $120,230 a year. The full range runs from $67,240 at the 10th percentile to $199,130 at the 90th — entry pay sits closer to the lower figure, and experience, licensing and specialisation move you up the range.
Can you become a data scientist without a degree?
Not usually — this occupation sits in preparation zone 4, where the typical entry route is most of these occupations require a four-year bachelor's degree, but some do not. The education breakdown above shows what people in the role actually reported.
Is data scientist in demand?
Federal projections expect employment to grow by about 34% between 2024 and 2034 — growing much faster than average. Openings also come from people retiring or changing jobs, which the growth figure does not count.
Skills and knowledge you need
Core skills
- Mathematics4.4/5
- Critical Thinking4.3/5
- Reading Comprehension3.9/5
- Speaking3.6/5
- Active Learning3.6/5
- Active Listening3.5/5
- Writing3.5/5
Knowledge areas
- Mathematics4.5/5
- Computers and Electronics4.2/5
- English Language3.0/5
- Engineering and Technology2.9/5
Transferable strengths: Complex Problem Solving, Programming, Judgment and Decision Making.