TLDR
You are staring at an offer, or maybe just googling out of curiosity, and you searched Data Scientist Salary by Experience Level (US) hoping for one clean answer. Instead you got five different numbers from five different sites, and not one of them told you exactly where you stand.
That gap is not harmless. Undersell yourself at year three because you trusted the wrong average, and by year seven you could have left tens of thousands of dollars on the table without ever knowing it.
I pulled the real 2026 figures from Glassdoor, PayScale, ZipRecruiter, Indeed, and the Bureau of Labor Statistics, then broke them down stage by stage so you know exactly where you land right now. For a full picture of how tech pay compares across roles, WhatIsTheSalary is a good place to start before you dig into the numbers below.
Why the Numbers Never Agree
Glassdoor pulls from self-reported employee data, so it skews toward larger companies where employees are more likely to submit a number. PayScale leans on individual salary surveys, which often run slightly lower because they include smaller employers and non-tech industries.
ZipRecruiter and Indeed pull from active job postings, so their numbers reflect what companies are offering right now rather than what current employees already earn. The Bureau of Labor Statistics uses employer-reported payroll data, the most rigorous method but also the slowest to update, with its latest full release from May 2024.
None of these sources are wrong. They are measuring slightly different things, which is why I am giving you a range from each instead of picking one number and calling it the truth.
Average Data Scientist Salary in the US, by Source
| Source | Average Base Salary | Typical Range | Data Basis |
| PayScale | $103,743 | $73,000 to $145,000 | 5,814 salary profiles, updated May 2026 |
| ZipRecruiter | $122,738 | $98,500 to $173,000 | Active postings, updated August 2026 |
| Glassdoor | roughly $126,000 | $84,000 to $179,000 (entry to senior) | Self-reported employee pay, 2026 |
| Indeed | $131,121 | $80,500 to $213,570 | 6,900 postings, past 36 months |
| Bureau of Labor Statistics | $112,590 (median, adjusted) | Not broken out by level | May 2024 OES release, plus 2026 drift estimate |
If you want a single working number for 2026, $118,000 to $126,000 base is a reasonable midpoint across all five sources. For a deeper look at how this compares across the broader data science field, our data scientist salary in the US guide breaks the national picture down further by industry and company size.
Salary by Experience Level
Entry Level (0 to 2 Years)
Fresh graduates and career switchers typically start between $75,000 and $95,000 in base salary. PayScale puts early career professionals with one to four years of experience at an average total compensation of $101,971.
This tier has felt the most pressure in 2026. A lot of the SQL pulls, exploratory plots, and basic feature engineering that used to be handed to a junior hire are now done faster with AI coding assistants, so some companies are hiring fewer pure entry level roles and asking mid level hires to cover both.
Mid Level (3 to 6 Years)
This is where the range widens fast. Nationally, mid career data scientists earn somewhere between $115,000 and $175,000 depending on location and employer type. In expensive tech metros like Los Angeles or San Francisco, that same band shifts up to $154,000 through $218,000.
At this stage you are usually building predictive models independently and starting to work directly with stakeholders outside the data team.
Senior (7 or More Years)
Senior data scientists nationally land between $157,000 and $210,000 in base pay, with total compensation at FAANG-level companies commonly reaching $200,000 to $290,000 once bonuses and equity are added. At this point you are expected to set technical direction and mentor junior staff, which is a different job than year two even if the title still says data scientist.
Principal, Lead, and Head of Data Science
Once you cross into principal or head of data science territory, total compensation at major tech and finance employers regularly clears $250,000, and figures above $300,000 are not unusual once bonuses and stock are fully vested. A Director of Data Science role can push past $250,000 in base alone before any variable pay is added.
How This Compares to Related Data Roles
Data scientist pay usually runs 30 to 60 percent above a comparable data analyst role at the same experience level. A mid career analyst earns roughly $85,000 to $120,000, while a mid career data scientist in the same window earns $130,000 to $175,000.
If you are weighing the two paths, or you are an analyst deciding whether the jump to data science is worth the retraining, our data analyst salary by experience level guide walks through that same progression for the analyst track.
For the full current picture of analyst pay across every major US market, our Data Analyst Salary in the US 2026: Complete Guide covers it in full, including how the analyst-to-data-scientist transition plays out in real offers.
Total Compensation vs Base Salary
Here is a mistake I see constantly. Someone gets an offer for $130,000 base and turns it down for a competing offer of $140,000 base, without ever looking at total compensation.
Total comp includes base salary, signing bonus, annual performance bonus, and, at public companies, restricted stock units that vest over a set schedule, usually four years. A $130,000 base offer with $60,000 in RSUs vesting over four years and a $15,000 signing bonus is worth far more in year one than a flat $140,000 base with no equity.
Check the vesting schedule specifically. Some companies front load the first year, others back load it, and that difference changes your actual take home for the next several years.
What Actually Moves Your Number
Location is still the single biggest lever. San Francisco data scientists average close to $180,000 to $198,000, Seattle sits around $156,000 to $165,000, and mid tier metros like Austin, Denver, and Charlotte land in the $130,000 to $145,000 range with a noticeably lower cost of living.
Industry matters almost as much. Finance and top tier tech pay well above the national median, while healthcare and traditional retail sit closer to it or below.
Skills matter too. In 2026 the ones with the clearest salary impact are generative AI and large language model experience, cloud platform work across AWS, GCP, and Azure, MLOps and production deployment, and data engineering fundamentals. A data scientist who can ship a model into production, not just build one in a notebook, gets paid differently than one who cannot.
If data science is not the only path you are weighing, other technical careers follow a similar climb. Cybersecurity is a good comparison. Someone can start as a cybersecurity analyst without a degree, follow a defined cybersecurity career path upward, and eventually reach the pay covered in our CISO salary guide, which sits comparable to what a principal data scientist earns at the top of that track.
Common Misconceptions
“A PhD always pays more than a master’s degree.” Not automatically. Past a certain seniority level, demonstrated project impact and production experience carry more weight than the degree itself.
“Remote roles pay less.” Some companies apply a 10 to 15 percent location adjustment, but many do not. Remote mid level pay nationally sits around $141,000 to $180,000, competitive with plenty of in-office roles outside the top three metros.
“Data scientist and data analyst are the same job with a different title.” They overlap early on, but the pay gap widens with experience because the data scientist track demands deeper statistics, machine learning, and programming depth.
“A bigger company always means a bigger paycheck.” Not always. A senior data scientist at a well-funded startup with meaningful equity can out-earn the same title at a large company with a flatter compensation band.
Salary Growth Timeline
Here is what growth looks like for someone managing their career deliberately. Year zero to two, you sit in the $75,000 to $95,000 range. Year three to six, you move into the $115,000 to $175,000 band as you take on independent ownership. Year seven and beyond, base pay moves into the $157,000 to $210,000 range, with total comp often well above that at larger employers.
Changing companies strategically, specializing in a high demand area like MLOps or applied AI, and negotiating your level correctly at hire all accelerate that climb. Staying at one employer for six or more years without a title change, or accepting an under-leveled offer just to end a long interview process, slows it down.
When to Stop Researching and Start Negotiating
At some point, more research is just procrastination dressed up as due diligence. If you have a real offer in hand, here is what matters.
Get any competing offers in writing before you go back to the recruiter, since a verbal offer carries no weight. If base salary feels fixed, ask about the signing bonus or equity grant instead, since those are usually more flexible. Always ask rather than demand, and frame it around market data, not personal need. Negotiate after you have the offer and before you accept, not after you have already said yes verbally.
Frequently Asked Questions
What is the average data scientist salary in the US in 2026?
The average sits between $103,000 and $131,000 in base salary depending on the source, with a working midpoint of roughly $118,000 to $126,000.
How much do entry level data scientists make?
Entry level base pay typically runs $75,000 to $95,000, with total compensation closer to $100,000 once early bonuses are included.
Do data scientists make more than data analysts?
Yes, typically 30 to 60 percent more at comparable experience levels, largely due to deeper statistics, programming, and machine learning requirements.
What state pays data scientists the most?
Washington currently leads, with New York and the District of Columbia close behind.
Is data science salary growth slowing down in 2026?
Growth has stayed strong for mid and senior roles, but entry level hiring has tightened as AI tools absorb more basic exploratory work.
Does a master’s degree increase data scientist pay?
It helps at the entry level, but past the mid career mark, production experience and project ownership matter more than the degree itself.
Share Your Experience
If you have negotiated a data scientist offer recently, or a company surprised you with what they came back with, I would genuinely like to hear about it. Real numbers from real offers are what keep guides like this accurate, so feel free to share yours in the comments.
How This Article Was Created
The figures in this guide come from Glassdoor, PayScale, ZipRecruiter, Indeed, and the Bureau of Labor Statistics, current as of 2026, with the BLS baseline drawn from its May 2024 release and adjusted for typical annual compensation drift. No numbers were invented or estimated without a cited source. This article was written to help job seekers understand real market pay, not to recruit for any employer or platform.
Shahzada Muhammad Ali Qureshi (Leeo)
I’m Shahzada — a software engineer by education and an SEO professional by trade. I built WhatIsTheSalary.com to go beyond just showing salary numbers — every page is manually researched across sources like BLS, Glassdoor, LinkedIn Salary, and PayScale to give you the full picture in one place. If you found what you were looking for here, that’s exactly the point.
