Data analyst salary in 2026: the spread and the industries

BLS put the median annual wage for data scientists at $120,230 - $57.80 an hour - in May 2025, and that is the code most jobs advertised as Data Analyst are counted under. The middle of the occupation is not the middle of your search, though. The lowest tenth of that same occupation earned under $67,240 and the highest tenth over $199,130, and which end you sit near has more to do with the industry writing the check than with the word in front of "Analyst" on the posting.

Which occupation is a "data analyst" in the federal data?

None of them, exactly. The Standard Occupational Classification has no code called Data Analyst, so a posting with that title is counted wherever the employer's actual job fits best - and several codes are plausible. O*NET files Business Intelligence Analysts as 15-2051.01, a specialty inside data scientists, and the sample titles it lists for that code include Business Analyst, Business Intelligence Analyst, Market Intelligence Analyst and Competitive Intelligence Analyst. Its core tasks are the recognisable ones: generate standard or custom reports summarising business, financial or economic data; maintain or update dashboards and databases; provide technical support for existing reports.

A recurring-reporting job at an insurer and a forecasting job at a software firm can both be posted as Data Analyst and land in different codes. The medians are far apart.

Where a Data Analyst posting gets counted, May 2025

Median annual wage and the 10th-90th percentile range for the five occupations a Data Analyst title most often falls into. BLS Occupational Outlook Handbook, May 2025 estimates; each occupation's page is listed under sources.

	Median annual wage	10th percentile	90th percentile
Data scientists (15-2051)	$120,230	under $67,240	over $199,130
Computer systems analysts	$105,850	under $67,340	over $167,710
Management analysts	$101,860	under $60,640	over $171,640
Operations research analysts	$88,940	under $57,060	over $159,910
Market research analysts	$78,760	under $43,390	over $155,480

Two rows are worth separating. Data scientists is the code that contains the business-intelligence specialty most day-to-day analyst work resembles - SQL, dashboards, a weekly report someone reads on Monday. Market research analysts, at a $78,760 median, is where an analytics job inside a marketing team frequently lands, and it is by far the biggest of the five: 952,700 jobs in 2025, against 275,600 data scientists. If you are quoting a $120,230 median while applying to marketing analytics roles, you are quoting the wrong row by more than forty thousand dollars.

There is a quick test for which row is yours, and it is the task list rather than the title. O*NET's core tasks for data scientists (15-2051.00) are "analyze, manipulate, or process large sets of data using statistical software", "test, validate, and reformulate models to ensure accurate prediction of outcomes" and "recommend data-driven solutions to key stakeholders". The Business Intelligence Analysts specialty underneath it reads differently: generate standard or custom reports, maintain dashboards and databases, manage the timely flow of business intelligence to users, support existing reports. Both sit under the same wage estimate. But if a Data Analyst posting describes campaign measurement and survey work with no modelling in it, the market research analyst row is the closer comparison, and the number you should be carrying into the conversation is lower.

How wide is the range within one occupation?

How to read this. The median is the middle worker, not the average - half the people BLS counted in this occupation earned more than $120,230 and half earned less, and a handful of very large salaries cannot drag it upward the way they would an average. The $131,890 between the tenth and ninetieth percentiles is not a career ladder either. It is one photograph of everybody in the occupation at once: the analyst two years out of a statistics degree and the one running a modelling team at a bank are both inside that column, along with every industry and every metro area in the country.

What the percentiles do not carry is years of experience. BLS does not publish an experience breakdown for this occupation, so nothing here tells a Data Analyst with three years of SQL behind them what the third year was worth. It tells them the shape of the pool they are being priced inside, which is a different and less satisfying thing.

The hourly figure is worth keeping in your notes if any of your search is contract work. BLS reports the same May 2025 median two ways for this occupation, $120,230 a year and $57.80 an hour, and the annual figure is the one that gets quoted. A Data Analyst weighing a contract rate against a salaried offer needs the hourly one, and needs to remember what BLS is counting. The $57.80 is a wage. It excludes the employer-paid benefits that sit on top of a salaried job and that a contract rate has to buy for itself, so an hourly contract quote matching it is not an even trade.

Why there is no city table in this post

Because there is no longer a page to read one from. The per-occupation OEWS addresses that salary articles have linked to for years - bls.gov/oes/current/oesNNNNNN.htm - now redirect to the OEWS tables index. I opened the one for 15-2051 while writing this and landed on the index, which offers metropolitan and nonmetropolitan estimates for May 2025 as downloadable files and data-tool queries, not as a readable page per occupation.

That leaves two honest options and one dishonest one. You can pull the metro file yourself for a specific code and read the figure for your area, which is a real answer for data scientists or for market research analysts. You can use the national percentile range above and treat cost of living as a separate adjustment you make deliberately. What nobody can do is publish a tidy city-by-city table under the title "Data Analyst" and call it a federal figure, because that is two approximations stacked: a code that is not your title, filtered to a metro area that groups your city with its entire commuting zone.

Industry moves the number more than seniority does

Median annual wage for data scientists by industry, May 2025

The five industries BLS lists for the occupation. One occupation code, one month, five different medians.

Publishing, broadcasting, and content providers		$142,240
Computer systems design and related services		$132,380
Credit intermediation and related activities		$129,490
Management of companies and enterprises		$128,050
Insurance carriers and related activities		$108,650

The distance between the top and bottom bars is $33,590, and every worker behind them holds the same occupation code in the same month. Set that against the distance between codes, holding the data scientist median as the fixed point.

Arithmetic on the May 2025 medians in the Occupational Outlook Handbook, one page per occupation, all listed under sources.

Three of those four occupation switches move the median less than staying put and changing industry does. Only the fall to market research analysts moves it further. That is the finding I would act on. For guessing what a given Data Analyst posting pays, the employer's industry is a better clue than the seniority word in the title, and it is the one piece of information every posting gives you for free.

It is worth being precise about what the comparison proves. The industry table cannot separate a pay premium from a staffing mix: publishers and content providers may pay data scientists more per head, or they may employ more senior ones, and BLS reports the median for each industry rather than the composition behind it. The practical use survives either way. If two postings for recognisably the same reporting work sit in front of you, one at an insurance carrier and one at a computer systems design firm, the second is the higher-median environment whatever the mechanism turns out to be.

Does a master's degree change the number?

O*NET's respondents for data scientists (15-2051.00) split 48 percent bachelor's and 44 percent master's; for the Business Intelligence Analysts specialty where Data Analyst titles cluster, it is 68 percent bachelor's and 23 percent master's. BLS lists a bachelor's degree as the typical entry-level education for the occupation, with no prior work experience and no on-the-job training required. Those percentages describe who holds the job. Neither source reports pay by education level, so no honest reading of them gives you the value of the degree.

Where the postings actually are

Growth rate and volume are different questions, and the second is the one that fills your week. The Occupational Outlook Handbook projects employment of data scientists to grow 35 percent from 2025 to 2035, the fastest of the five codes here, producing about 24,800 openings a year on a base of 275,600 jobs. Market research analysts are projected to grow 7 percent across the same decade - a fifth of that rate - and still produce about 82,000 openings a year, because 952,700 people already do the work and a share of them leave it every year. Management analysts, at 10 percent growth on 1,077,100 jobs in 2025, are projected to produce about 94,100 openings a year.

So a Data Analyst who searches only the fastest-growing corner of the market is fishing in the smallest pond of the three. The dashboards-and-reporting job that reads as data analysis is advertised across all of them, and two of the three carry more openings than the one with the headline growth rate. Openings are not the same as vacancies you can apply to today, either: the Handbook's annual figure counts growth plus the people leaving the occupation, projected across a decade and then averaged, so it is a measure of how often a seat comes free rather than a count of live postings.

One caution about mixing figures from these sources. Every projection above comes from the 2025-35 vintage published in the Handbook. O*NET is still showing the previous 2024-34 series for the same code - 245,900 employed and 23,400 projected openings, against the Handbook's 275,600 and 24,800 - and reading the difference as a year of growth would be an artefact of the vintage rather than anything about the occupation. Check the year range on the projection before you quote it, the same way you check the month on a wage.

What these numbers do not tell you

They are estimates of what people were paid as of May 2025, not what employers are offering now, and a posted range is a negotiating position rather than a payroll observation. They cover wages and salaries, so equity, bonus and any shift differential sit outside them entirely. They are national figures that pool every metro area and every industry into one number, except where the industry table breaks it out. And the largest limit is the one this post opened with: not one of these estimates is for a job title called Data Analyst, because that title does not exist in the classification. Every figure here is the code your work is nearest to, which is useful and is not the same as exact.

If you are applying for this role

Three specifics.

Search the title variants, not the title. O*NET's sample titles for 15-2051.01 give you the list employers actually post under: Business Intelligence Analyst, Business Analyst, Market Intelligence Analyst, Competitive Intelligence Analyst. Add Operations Research Analyst where the work involves optimisation and Market Research Analyst where it sits inside a marketing team. One job, five spellings.

Expect a range, and know which range applies. If the work is dashboards and modelling at a technology or finance employer, the relevant national picture is the data scientist one: $120,230 median, under $67,240 at the tenth percentile, over $199,130 at the ninetieth, all May 2025. If it is survey and campaign analysis at a consumer brand, price it against market research analysts at $78,760 and make the metro adjustment yourself.

Ask one question on the first call. "Which job family and level does this req sit in, and what is the band for that level?" A recruiter can answer that in a sentence, and the answer converts every national median above into the specific number that will govern your offer. If the answer is that the req sits in a marketing family rather than a data or engineering one, you have learned something the job title was never going to tell you.

Once the search list is settled, the bottleneck stops being research and becomes the forms. HeroApply fills the application from your resume, so the hours go into the portfolio piece a hiring manager will actually open.