Data Scientist Pay Hits $118,413 as Unemployment Rises to 4.2%

A Strong AI Job in a Weak Labor Market

The U.S. labor market is pulling in two directions this fall. A small set of AI-linked roles keeps growing and paying well, while overall hiring has nearly stopped and wages are falling behind prices. Data scientist is the clearest example of the first trend. Recent CBRE figures put the average salary for the role at $118,413, and the best-paid positions go above $300,000.1 The same figures show data scientist jobs grew 12.4% in 2025, while total U.S. tech employment grew only 1.8%.1

The broader picture looks very different. Employers added just 29,000 jobs in September, and the unemployment rate rose to 4.2% from 4.1%, according to the Bureau of Labor Statistics.23 Average hourly earnings grew 3% over the year, the slowest annual pace since May 2021.23 Tech layoffs are also on pace to beat last year's total, depending on which tracker you use.1214 Taken together, the data shows a market where a few specialists can still name their price and most other workers are losing ground.

The Data Scientist Numbers

According to CBRE's research, demand for data scientists is strongest in three areas: the technology sector, professional and business services, and finance, insurance and real estate (FIRE).1 FIRE has added more than 90,000 tech jobs since 2022, more than any other U.S. industry. Within FIRE, data scientist postings rose about 13.8%, or roughly 5,870 new openings.1 Advertised pay at the top is very high. Listings cited include up to $322,820 for a senior data scientist at Roblox and up to $272,000 for a staff role at Toast.1

Other labor data supports the trend but disagrees on the details. A Veritone analysis of early 2025 found data scientist was among the three AI job titles with the most openings, but it measured year-over-year growth at 10%, below CBRE's 12.4%.7 The Bureau of Labor Statistics projects data scientist employment will grow 33.5% between 2024 and 2034, far faster than the average for all occupations.6

Salary estimates also vary widely. Veritone put the median salary for AI roles overall at $156,998 in the first quarter of 2025.7 DataCamp's analysis of two million job postings found the average U.S. AI engineer earns about $113,347.8 By that measure, the $118,413 data scientist average sits near the middle of AI pay, not the top. The figures depend on who is counted, so they are best read as a range.

On growth, data science is not the fastest-rising title. DataCamp found AI engineering postings jumped 255% year over year, and AI and data postings overall rose 80%.8 LinkedIn's 2026 Jobs on the Rise report also named AI engineer the fastest-growing job title in the U.S.2 Data science grows more slowly, but it is an established job that companies across many industries already know how to hire for. That likely makes it a sturdier career than newer roles built mainly on startup funding.

Unemployment Rises, With a Caveat

September's jobs report missed forecasts by a wide margin. Economists surveyed by Dow Jones expected 84,000 new jobs, and those polled by Reuters expected 90,000.25 Revisions made it worse. July changed from a gain of 21,000 jobs to a loss of 10,000, and August was cut from 162,000 to 133,000, for a combined reduction of 60,000.29 The three-month average of job gains is now about 51,000.29

The rise in unemployment is less alarming than it first looks, and the coverage largely agrees on why. CNBC and the Mortgage Bankers Association both said the increase came mainly from more people entering the labor force to look for work.2328 The labor force grew by 485,000 and participation rose to 61.8%, the highest since May.23 A broader measure that includes discouraged workers and involuntary part-timers fell to 7.6%, its lowest since January 2025.23 The New York Times also pointed out that the jobless rate has stayed at or below 4.5% since October 2021, the longest such streak in modern history.22

Unemployment is not the main problem in this report. Weak job opportunities are. The Times noted that the average unemployed worker has been searching for nearly six months, and that low job-switching suggests workers see few openings.22 Job openings are near an eight-year low outside the pandemic, while layoffs measured across the whole economy stay historically low.26 Economists call this a low-hire, low-fire market.25

Wages Are Falling Behind Prices

Wage data is the clearest weak spot. Average hourly earnings for private-sector workers rose just 5 cents in September to $37.81, below the consensus forecast.27 Since April, prices have risen faster than pay, which means real wages are falling.29 August inflation measured by the PCE index was 3.4% over 12 months, with core PCE at 3%.28 The Times linked rising inflation to the war in Iran.22

Based on that $37.81 average, a full-time worker earns roughly $78,600 a year. The average data scientist earns about 50% more. Slowing overall wage growth makes that gap wider, not smaller.

Other measures point the same way. The Employment Cost Index showed wages and salaries up 3.1% in the year to June 2026, down from 3.5% in the year to March.21 Fifth Third economist Bill Adams said slowing pay while inflation speeds up suggests workers are struggling to move into better-paying jobs.30

The report also matters for interest rates. The Federal Reserve raised its target range by a quarter point to 3.75%–4.00% in September.24 After the weak jobs data, markets bet heavily that the Fed will hold rates at its October meeting.23 Navy Federal's Heather Long said she still expects a December hike.23 The September inflation report on October 14 is the next key test.30

Tech Layoffs Keep Coming

Tech layoffs this year are large, but the trackers disagree on how large. Layoffs.fyi counted 123,305 tech workers laid off across 289 companies by September 2, which already passed last year's total.12 TrueUp counts more broadly and reports 193,698 people affected across 643 layoffs so far in 2026, compared with 245,953 in all of 2025.14 Both show heavy job cuts. They differ on whether 2026 is a record year.

The biggest cuts came from large, profitable companies: Oracle at about 21,000, Amazon at 17,267, Dell at 11,000, Meta at 10,400 and Microsoft at about 4,800.12 Recent announcements include HubSpot cutting about 660 jobs, roughly 7% of its staff.11 Netflix is cutting 850 jobs and Amazon another 1,000.14 Kroger plans to eliminate 3,000 corporate roles as it expands its use of AI.15

Companies are sending mixed messages about AI's role. HubSpot described its restructuring as part of a shift toward AI-driven customer outcomes, yet CEO Yamini Rangan said the cuts were not driven by AI efficiencies.1116 The cuts came even though HubSpot's revenue grew 20% last quarter.16 Microsoft has also rejected the idea that its cuts mean AI is replacing staff.12 Amazon is cutting corporate jobs while spending about $200 billion on AI infrastructure this year.13 Whatever companies say, the money is moving from staff to computing power.

Zoho's Sridhar Vembu made that link directly. He said rising AI costs, including a fourfold jump in server prices, led the company to freeze annual raises and cut marketing.19 He described the outlook for software jobs as grim and said some customers are replacing Zoho products with tools built through AI-assisted "vibe coding."19

What the Gap Means

The $118,413 headline needs context. Data scientists are not immune to cuts. Adidas's tech hub layoffs in Gurgaon included data scientists and data engineers.12 FIRE is credited with adding tens of thousands of tech jobs since 2022, yet financial-activities employment overall has fallen by 129,000 since its May 2025 peak, including 7,000 jobs in September.127 The same sector is hiring data specialists while cutting many other roles.

This is the clearest takeaway from the data. AI is not creating broad job growth. It is moving pay and hiring toward a smaller group of workers with technical skills, while hiring is flat and real wages are falling for nearly everyone else. Hiring managers keep saying AI fluency is a top priority, and the gap between people who have those skills and people who don't is growing.9 For job seekers, the strong data scientist numbers are real but narrow. Even in this field, workers should expect long job searches as companies shift spending from people to computing.