Strong • Lead or Specialist

Data Scientist.

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.

Salary$112,590per year
Openings23,400per year
Growth+34%10 year

Example job titles

Data ScientistMachine Learning EngineerData Analytics ManagerBusiness Intelligence AnalystAnalytics EngineerData AnalystAI/ML Scientist

Why This Rating.

[01]

This role is strong

Data scientists face a double-edged situation: AI tools are rapidly automating the core technical tasks of building models, cleaning data, and running analyses that define much of this work today. However, the role is evolving toward directing and validating AI systems, translating business problems into the right technical approach, and interpreting results for decision-makers-skills that keep experienced practitioners valuable. The lack of any licensing requirement or physical presence means the purely technical side of the job is highly exposed, and the role's long-term resilience depends on shifting toward strategic AI oversight rather than hands-on model building.

Risks & Opportunities.

[02]
[01] Risks
60%

of data prep and feature engineering now handled by AutoML tools[1]

Exploratory data analysis, feature engineering, and initial model selection - work that junior data scientists and analysts spend significant time on - are tasks that AI tools now handle reliably and quickly [U.S. Bureau of Labor Statistics, Sep 2025]. AutoML platforms and AI-assisted analysis tools are automating the mechanical parts of the data science workflow, which concentrates demand at the senior end of the role where domain expertise and business judgment drive the work. BLS projects 34% employment growth, but hiring patterns suggest that demand is shifting toward data scientists who can translate complex model outputs into organizational decisions, not those who optimize model parameters.

[02] Opportunities
23,400

annual job openings, among the highest of any STEM occupation[2]

This role scores a 5 out of 5 on directing AI tools - the highest rating - reflecting that data scientists who use AI to run faster experiments, test more hypotheses, and explore larger datasets are producing more output than those doing the same work manually [U.S. Bureau of Labor Statistics, Sep 2025]. Domain expertise in healthcare, finance, climate science, or other specialized fields is what differentiates senior data scientists from AI tools and from each other. BLS projects 34% employment growth through 2034, among the strongest projections for any occupation, driven by organizations needing people who can interpret data model outputs and make consequential decisions based on them.

Observed AI Impact.

[03]

AI is starting to automate these

Share of AI conversations where this task is handled solo, with little human involvement.

Solve business problems with data
Identify solutions to business problems, such as budgeting, staffing, and marketing decisions, using the results of data analysis.
61.4% automated
Med usage
Raw Data Cleaning and Manipulation
Clean and manipulate raw data using statistical software.
58.6% automated
Med usage
Write analysis functions/apps
Write new functions or applications in programming languages to conduct analyses.
58.4% automated
High usage
Propose math-based solutions
Propose solutions in engineering, the sciences, and other fields using mathematical theories and techniques.
52.3% automated
Med usage

AI assists but needs guidance

Share of AI conversations where this task is handled collaboratively, with a human steering.

Recommend data-driven solutions
Recommend data-driven solutions to key stakeholders.
69.6% augmented
Med usage
Identify trends/relationships
Identify relationships and trends or any factors that could affect the results of research.
65.4% augmented
Med usage
Visualize analysis results
Create graphs, charts, or other visualizations to convey the results of data analysis using specialized software.
57.4% augmented
High usage
Validate predictive models
Test, validate, and reformulate models to ensure accurate prediction of outcomes of interest.
55.1% augmented
Med usage
Analyze large datasets
Analyze, manipulate, or process large sets of data using statistical software.
50% augmented
Med usage

AI hasn't figured these out

Low or no AI usage recorded for these tasks.

Apply feature selection algorithms
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.
No data

Data: Anthropic Economic Index (Jun 2026) · Real-world Claude usage patterns across occupations

How to Adapt.

[04]
[01] Already in this role?

The parts of this role most resistant to displacement are problem formulation and decision translation - identifying which questions are worth asking with data, and communicating what model outputs actually mean for business or research decisions. Build depth in a specific domain (healthcare, finance, climate, operations) so that your value comes from understanding the context of the data, not just the mechanics of the analysis [U.S. Bureau of Labor Statistics, Sep 2025]. Over the next six months, get comfortable using AI tools to accelerate the EDA and preprocessing work, which frees more time for the judgment-intensive interpretation and stakeholder communication that AI does not handle well.

“AI coding tools have shifted the nature of data work — the time savings show up most in exploratory analysis and iteration cycles, not in the judgment work of framing a problem correctly or deciding which model output to trust. The data scientists who are thriving are treating AI as a fast intern: useful for first drafts, requires supervision.”

GitHub Octoverse 2024, GitHub

“Data scientists represent one of the occupations most actively using AI tools in their work, with augmentation patterns dominating over pure automation — meaning AI is handling the computation and iteration while humans direct the analysis and interpret results.”

Anthropic Economic Index, Anthropic

[02] Thinking of entering?

Most entry-level data scientist positions require at minimum a bachelor's degree in statistics, math, or computer science, and graduate degrees are common for research and senior roles [U.S. Bureau of Labor Statistics, Sep 2025]. The portfolio that gets hired shows end-to-end project work: data cleaning, modeling, and a clear explanation of what the findings mean for a real problem. Domain knowledge matters more as AI tools commoditize general-purpose data analysis - specialize in a field where you understand the data's context, not just its structure.

“The data science job market has matured: employers are now distinguishing between data scientists who can build models and those who can translate model outputs into business decisions. The latter is significantly harder to hire and commands a persistent premium.”

GitHub Octoverse 2024, GitHub

“The most-used data science tools in industry are Python, SQL, and Jupyter notebooks — and 76% of developers are now integrating AI assistants into their workflow. Candidates who can demonstrate working with AI-assisted data pipelines, evaluate model outputs critically, and document their methodology rigorously will stand out as AI tools raise baseline productivity expectations.”

Stack Overflow Developer Survey 2024

The Career Map.

[05]

The full BLS career track, plus relevant emerging AI-native paths. Click any role to see how to transition to it.

Entry

Computer Programmer

15-1251.00

Risky
Mid-Level

Web Developer

15-1254.00

Risky

Web Designer

15-1255.00

Strong

Web Administrator

15-1299.01

Exposed

Software QA Analyst

15-1253.00

Risky

AI Product Analyst

✦ Emerging

Senior

Software Developer

15-1252.00

Strong

Database Architect

15-1243.00

Solid

Information Security Analyst

15-1212.00

Strong

ML Engineer

✦ Emerging

Lead or Specialist

Data Scientist

★ This Role

Computer Systems Architect

15-1299.08

Solid

IT Project Manager

15-1299.09

Solid

Information Security Engineer

15-1299.05

Strong

Statistician

→ Lateral

Solid

Biostatistician

→ Lateral

Strong
Principal

Computer Science Researcher

15-1221.00

Strong

Sources

0.Data Scientist Occupational Data- O*NET Online

  1. 1.State of AI in the Enterprise- Deloitte Insights, 2024
  2. 2.Occupational Outlook Handbook: Data Scientists- U.S. Bureau of Labor Statistics, Sep 2025
  3. 3.Jobs on the Rise 2024- LinkedIn Economic Graph, Jan 2024
  4. 4.The state of AI in 2024- McKinsey & Company, May 2024