According to the U.S. Bureau of Labor Statistics (BLS), data scientists earned a median annual salary of $120,230 in 2025, with the range across a career running from under $70,000 for newcomers to well past $200,000 for principal-level talent. That spread is wide enough that “data scientist salary” alone does not tell you much about salary expectations until you know which stage of the career you are asking about.
Campbellsville University’s online Master of Science (M.S.) in Data Science and Artificial Intelligence program, a STEM-designated program that develops in-demand machine learning and AI skills, is tied to the fastest pay growth in the field. With a 100% online format, no GRE or GMAT requirement and the convenience of pay-by-the-course tuition, the program is specifically designed for working professionals looking to study on a flexible schedule.
This guide walks through what data scientists earn at each career stage, what separates senior pay from entry-level pay, how machine learning engineer salaries compare and which skills and industries pay the most. It also looks at how Campbellsville’s online M.S. program prepares graduates for these roles.
What Is the National Median Data Scientist Salary in 2026?
According to BLS, the median annual wage of $120,230 for data scientists sits well above the median across all U.S. occupations. The lowest-paid 10% of data scientists earn less than $67,240 a year, while the highest-paid 10% earn more than $199,130, and employment in the field is projected to grow 35% between 2025 and 2035, adding roughly 95,400 positions over the decade. That pace translates to about 24,800 job openings per year, factoring in both new positions and the need to replace workers who leave the field. Most of that growth is at the higher end of the pay range noted above, so career stage significantly shapes take-home pay.
O*NET OnLine, which gives the career a Bright Outlook designation, classifies data scientist roles under Job Zone Four, its category for occupations that need considerable preparation. Roughly 48% of data scientists hold a bachelor’s degree and 44% hold a master’s degree, per O*NET’s workforce survey, one reason a dedicated master’s degree is a common path into the field.
Data Scientist Salary by Experience and What They Earn at Each Career Stage
Career stage has more influence on data scientist pay than almost any other factor, and PayScale’s experience-based salary data shows why. PayScale tracks compensation across five experience bands, from less than one year in the field to 20 or more years, and pay climbs steadily and substantially at each step. The four stages below group that data into the career milestones most data scientists plan around.
Entry-Level Data Scientist (Less Than 1 Year)
A data scientist in the first year of the field averages $88,797 in total compensation, according to PayScale. That figure runs meaningfully above BLS’s reported 10th percentile of $67,240, though newcomers in smaller markets, nonprofit roles or public-sector jobs often land closer to that lower BLS benchmark before a track record accumulates.
Early and Mid-Career Data Scientist (1 to 9 Years)
Pay rises quickly once a data scientist moves past the first year. PayScale reports average total compensation of $102,115 for data scientists with one to four years of experience, then a jump to roughly $118,000 for those in the five-to-nine-year range, about 14% above the overall average PayScale tracks across all experience levels. This is typically when a data scientist moves from executing assigned analyses to owning full projects and mentoring newer hires.
Senior Data Scientist (10 to 19 Years)
Senior-titled data scientists average $137,549 in base salary, with base pay typically ranging from $108,000 to $171,000 and total compensation reaching as high as $181,000, per PayScale’s senior-title data. That is roughly 23% above PayScale’s all-experience average for the broader role, matching BLS’s reported jump into the profession’s upper income tiers.
Late-Career and Principal Data Scientist (20+ Years)
Data scientists with 20 or more years in the field average roughly 38% above PayScale’s overall benchmark, translating to total compensation in the neighborhood of $140,000 to $145,000. Lead and principal-level data scientists, along with those who negotiate equity at large technology employers, often clear BLS’s reported 90th percentile of $199,130 entirely, with total packages at major tech companies frequently exceeding $200,000 once stock compensation is included.
What Unlocks the Jump to Senior Data Scientist Salary Levels?
In-demand AI skills are what unlock the jump: PwC’s 2026 Global AI Jobs Barometer found that workers with those skills commanded a 62% wage premium over similar roles without them, up from 57% the year before, with jobs requiring specific AI competencies growing roughly eight times faster than the labor market overall. Experience alone does not fully explain that gap, since two data scientists with the same tenure can land in very different pay bands depending on their skill set and scope of responsibility. For a data scientist, that premium tends to appear right at the point where a role shifts from running standard analyses to owning production AI systems and leading how a team uses them.
The specific skills behind that premium are fairly consistent across the profession. Large language model (LLM) engineering, MLOps practices for moving models into production, deep learning frameworks such as PyTorch and TensorFlow and cloud platforms such as AWS SageMaker and Google Vertex AI now separate data scientists who command senior pay from those who do not.
The World Economic Forum’s Future of Jobs Report 2025 found that AI and big data skills posted one of the largest jumps in importance of any skill category tracked, a 17 percentage-point increase since 2023, with more than 90% of employers in top industries expecting to rely on it even more by 2030. The curriculum in Campbellsville’s online M.S. in Data Science and Artificial Intelligence program, develops these skills through coursework that pairs core data science with dedicated units in applied AI and big data analytics.
Industry adds another layer on top of skills and tenure. BLS reports that data scientists in publishing and broadcasting earn a median wage of $142,240, the highest of any major employing industry, followed by computer systems design services at $132,380 and credit intermediation, which covers banks and lenders, at $129,490. PwC’s research points to a similar pattern for AI-skilled workers broadly. The AI wage premium reaches 118% in consumer-facing industries but falls to just 16% in government and public-sector work, so industry choice can shift total pay almost as much as skill choice.
Machine Learning Engineer vs. Data Scientist Salary, Which Pays More?
Machine learning engineers tend to out-earn data scientists with comparable experience, and the difference comes down to what each role is responsible for. A data scientist focuses on analysis, statistical modeling and generating insight from data, often stopping once a model proves a hypothesis or informs a decision. A machine learning engineer picks up from there, taking a model into production and handling the engineering work of deploying, scaling and maintaining it inside live systems. That extra layer of software engineering depth is why the two roles, despite overlapping coursework and often overlapping job postings, land in different pay bands.
BLS classifies most machine learning engineering and AI research work under computer and information research scientists, a category with a median annual wage of $140,300, about 17% above the $120,230 median for data scientists broadly. That category is also projected to grow 22% from 2025 to 2035, adding roughly 2,900 openings a year, well below the 24,800 annual openings projected for data scientists. The practical takeaway is that machine learning engineering pays a premium, though data science remains the far larger and faster-growing field, with more than eight times as many annual openings.
How Campbellsville’s M.S. in Data Science and AI Positions You for These Salary Levels
Campbellsville University’s online M.S. in Data Science and Artificial Intelligence program prepares professionals to advance toward the pay premiums covered above. The 12-course curriculum includes dedicated coursework in artificial intelligence and machine learning, big data analytics, data mining and warehousing and applied AI, along with a capstone project that lets students apply those skills to an analytics or AI problem before graduating. The 36-credit-hour program carries a STEM designation, accepts up to 12 transfer credits, and applicants do not need a GRE or GMAT score to enroll.
The program is designed to be completed in about 12 months, considerably faster than the traditional two-year format many master’s programs in this field still use, so graduates reach the return on that investment sooner. Small, fully online class sizes let students work closely with faculty throughout the program. For a working adult who already has a foundation in data or technology work, that combination of a focused curriculum, current AI coursework and a compressed timeline is a practical way to move from an early-career salary band into the senior and specialized pay levels covered throughout this guide.
Data science is one path within Campbellsville’s broader computer science programs. Readers comparing degrees in that family can see how software development, cybersecurity and IT management careers stack up.
Ready to build the AI and machine learning skills behind senior-level pay?
Explore Campbellsville University’s online M.S. in Data Science and Artificial Intelligence program.
View ProgramPutting Data Scientist Salary Expectations to Work
Career stage remains the single biggest factor in data scientist pay, but the skills, role and industry effects covered above are what separate two data scientists at the same career stage from each other. The AI-skills premium rewards specific, learnable competencies rather than tenure alone, machine learning engineering roles command a further premium over general data science work, and industry choice adds yet another layer on top of both, pushing total compensation for some data scientists well above the profession’s median.
For a working professional weighing whether to invest in a formal credential, the data points in one direction: employers are paying a growing premium for exactly the skills a structured program can teach in a compressed timeframe. Campbellsville’s program is built around that premium, pairing core data science coursework with dedicated units in applied AI and big data analytics that map directly onto the skills driving the biggest pay jumps covered throughout this guide.
Learn more about Campbellsville University’s online Master of Science in Data Science and Artificial Intelligence program.
Frequently Asked Questions About Data Scientist Salary
The questions below cover some of the most common things people ask about data scientist pay and career progression before mapping out their own next move. Each answer draws on the salary and program details already covered above.
What is the average starting salary for a data scientist?
Entry-level data scientists with less than one year of experience average $88,797 in total compensation, according to PayScale.
How much does a senior data scientist make?
Senior-titled data scientists average $137,549 in base salary, with total compensation reaching as high as $181,000, per PayScale’s senior-title data.
Do machine learning engineers make more than data scientists?
Yes: BLS classifies most machine learning engineering work under computer and information research scientists, a category with a median annual wage of $140,300, about 17% above the median for data scientists.
Does Campbellsville’s M.S. in Data Science and Artificial Intelligence require the GRE or GMAT?
No, the program does not require a GRE or GMAT score for admission.
How long does it take to complete Campbellsville’s online M.S. in Data Science and Artificial Intelligence program?
Most students can complete Campbellsville’s program in about 12 months.
About Campbellsville University’s Online M.S. in Data Science and Artificial Intelligence Program
Campbellsville University traces its roots to 1906, when the Russell Creek Baptist Association founded Russell Creek Academy in Campbellsville, Kentucky. The school became a junior college in 1924, earned four-year accreditation in 1959 and reached university status in 1996 as its graduate programs expanded, including the data science and artificial intelligence offerings covered in this guide.
Campbellsville University is a Christian university based in Campbellsville, Kentucky, accredited by the Southern Association of Colleges and Schools Commission on Colleges (SACSCOC) to award degrees from the associate through doctoral level. The university has been recognized among the nation’s most affordable Christian colleges and holds a Military Friendly School designation, reflecting a long-standing commitment to accessible, service-oriented education.