Data Scientists Employment and Wage Statistics 2026

What the data scientists workforce benchmark shows

O*NET reports 245,900 workers in 2024 and a 2025 median annual employee wage of $120,230 for data scientists.

The 2024 to 2034 projection lists 23,400 openings and an outlook of much faster than average (7% or higher). Openings cover growth and replacement needs across the projection period.

Occupation-level figures do not establish which tools, methods, or business decisions a specific data role should own.

Define the data scientists role before recruiting

Write the role around analysis plans, documented datasets, reproducible models, validation results, and decision memos. A title and occupation code are useful references, but neither tells a candidate what evidence the employer expects each week.

Separate recurring work from occasional support. Name the systems, review points, deadlines, and decisions attached to each output.

State where independent judgment ends. Clear approval and escalation boundaries make the same role brief useful during screening and onboarding.

• Name the recurring outputs and their reviewers.
• List required source records and systems.
• Define decision and approval boundaries.
• Separate essential work from optional support.

Use a work sample that matches the job

A practical screening exercise can ask the candidate to inspect a small synthetic dataset, state its limits, and produce a reproducible analysis with one decision-oriented finding.

Give every candidate the same instructions, safe source material, time limit, and scoring rubric. Review the reasoning and the finished output against the requirements in the role brief.

A useful answer should also identify missing information and the point where the candidate would seek approval. That makes judgment visible without asking for unpaid production work.

• Use synthetic or redacted records.
• Score observable evidence.
• Keep the exercise narrow and time-bounded.
• Record the reason for each decision.

Build onboarding around the first controlled output

Start with data definitions, access controls, model review, and communication with decision owners. Show one complete example before asking the new hire to produce the same kind of work.

Assign a named reviewer and a question channel. Keep early permissions limited to the systems and records needed for the supervised task.

Review the first completed output against the hiring rubric. Record corrections, confirm escalation paths, and expand access only when the work requires it.

• Confirm the owner of each account and approval.
• Demonstrate one complete task.
• Review the first output with written criteria.
• Revisit temporary access after supervised work.

Use the benchmark without turning it into a hiring rule

The $120,230 median divides the national employee wage distribution in half. It is descriptive, not a required offer for every job carrying this title.

Compare the occupation definition with the actual location, industry, schedule, responsibility, and decision authority. If the job combines occupations, document that before choosing comparison data.

Keep the public benchmark and the employer's current hiring evidence separate. Record which source informed the role discussion and when the team checked it.

Read the limitations with the figures

Occupation-level figures do not establish which tools, methods, or business decisions a specific data role should own.

OEWS wage estimates exclude self-employed workers. The employee median cannot establish contractor compensation or predict what one candidate will accept.

Employment, median wages, outlook bands, and projected openings answer different questions. Preserve each figure's year, unit, and population whenever it appears in a role brief or decision memo.

Related research

Review the full research library, compare cluster coverage inside recruiting operations, and pair these findings with our VA candidate screening support.