JRIJob Risk Index

Profession JRI–51 / Technology

Will AI replace data scientists?

Data scientists transform raw data into meaningful insights using statistical software, machine learning, and visualization. They clean and manipulate large datasets, apply sampling techniques, and develop models to predict outcomes like sales or healthcare use.

The risk spectrum — where Data Scientist sits
Data Scientist vs the 82 other jobs
Risk rank51 / 83
Automation timeline5-10 years
Median salary$120,230
Projected growth+33.5% (2024–34)
01 / Job market

Official outlook: still growing.

Within the 83 professions
Salary$120,230
$31k$171k
Growth+33.5% (2024–34)
-25.9%33.5%

The U.S. Bureau of Labor Statistics projects a +33.5% change in employment for this occupation between 2024 and 2034, from a current base of 262,440 people employed earning a median of $120,230 a year.

Source: BLS Employment Projections 2024–34 & OEWS May 2025.

AI adoption in postings →

JRI demand index / weekly, base 100367
Aug 3Aug 10

Collected weekly through our own intake pipeline across live job postings; normalised index, not absolute counts.

02 / Real salaries

Data Scientist salaries by city

Median pay from real records (H-1B filings and tech job postings), across the cities with most observations.

New York$141,170Seattle$142,501San Francisco$169,000Bellevue$142,501Redmond$166,104San Jose$175,000

Range shows p25–p75; the dot is the median. Sources carry a documented bias — see the full salary page.

See real salaries →

03 / How to enter

How to become a data scientist.

Typical preparation

Job Zone Four: 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.

Job training

Employees in these occupations usually need several years of work-related experience, on-the-job training, and/or vocational training.

Getting in is one thing — the day-to-day runs on a specific set of tools and skills:

Skills employers ask for

From real job postings for this role — click to explore who asks for them.

Source: O*NET 30.0 database (CC BY 4.0).

06 / FAQ

What people ask.

01Will AI replace data scientists?
Data Scientists are rated medium risk. Automated tools may handle routine data processing within 5-10 years, while the role shifts toward critical evaluation and stakeholder communication. Projected growth of +33.5% (2024–34) suggests demand continues.
02How soon could automation affect Data Scientists?
Automation may affect Data Scientists within 5-10 years. Routine data processing and initial model building become automated first. The occupation is medium risk and employs 262440 people.
03What skills keep Data Scientists relevant?
Explainable AI and model interpretability techniques, plus data narrative development for non-technical audiences, are rated high demand. Human oversight of automated machine learning pipelines is medium demand. Designing experiments and validating model performance against business realities also matter.
04What preparation is needed to become a Data Scientist?
Most positions expect a four-year bachelor's degree, though not universally. Critical Thinking, Reading Comprehension, and Active Listening are rated high-demand for entry. Familiarity with tools like SAS and Apache Hadoop is typical.
05What related roles could Data Scientists pivot to?
Adjacent titles include Machine Learning Scientist, Research Scientist, and Applied Scientist. Alternative occupations are Natural Sciences Managers, Marketing Managers, and Management Analysts.
06Is Data Science a good career to start in 2026?
Starting in 2026, Data Science offers annual earnings of 120230. The occupation projects growth of +33.5% (2024–34) and currently employs 262440. Automation risk is medium, with changes expected within 5-10 years.
07What tasks or tools define a Data Scientist's work?
Typical tasks include maintaining a library of model documents, reviewing technical design documentation, and monitoring customers using business intelligence tools. Common tools are Amazon Web Services AWS software, C, C++, SAS, and Apache Hadoop.