Data scientist salary in the USA is one of the most searched career salary topics because data science has become an important part of technology, business, finance, healthcare, marketing, and many other industries. According to the latest U.S. Bureau of Labor Statistics data, the median data scientist salary was $120,230 per year in May 2025. That is about $57.80 per hour before taxes when converted to an hourly rate. Data scientist salary can be much lower for people just starting their career and much higher for experienced professionals, senior data scientists, and workers in high-paying technology markets. The lowest 10 percent of data scientists earned less than $67,240 per year, while the highest 10 percent earned more than $199,130. Salary also changes a lot by state. Washington has the highest reported median salary at $163,350, while Mississippi is at $69,490. This guide covers the average data scientist salary, data scientist salary per hour and month, starting salary, salary by state, experience, education, industries, and other important factors that affect data scientist pay in the USA.
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What Is the Average Data Scientist Salary in the USA?
The average data scientist salary can mean different things because salary websites may show an average, median, or salary range. For a useful comparison, the BLS median wage is a good number to look at because half of data scientists earn more and half earn less than the median.
In May 2025, the median annual wage for data scientists in the United States was $120,230. The national wage range is also quite wide. Data scientists in the lowest 10 percent earned less than $67,240, while the top 10 percent earned more than $199,130. This shows that data scientist pay can increase a lot with skills, experience, industry, location, and job responsibility.
| Data Scientist Salary Level | Annual Salary |
|---|---|
| Lowest 10% | Less than $67,240 |
| National Median | $120,230 |
| Highest 10% | More than $199,130 |
The median figure is more useful than simply calling one number the "average salary" because a small number of very high salaries can increase an average. For someone researching a data scientist career, it is better to look at the full salary range and also check the salary in the state where they plan to work.
Data Scientist Salary Per Hour
Many people searching for a data scientist salary also want to know how much a data scientist makes per hour. Based on the 2025 national median annual wage of $120,230, the median hourly wage is about $57.80 per hour.
The actual hourly pay can be different depending on the employer, location, experience, and type of work. A new data scientist may start below the national median, while an experienced data scientist working in a large technology company can earn considerably more.
- National median annual salary: $120,230
- Median hourly pay: about $57.80 per hour
- 10th percentile annual salary: $67,240
- 90th percentile annual salary: $199,130
Hourly salary is mainly useful for comparing data scientist pay with other jobs. Most data scientists are full-time salaried employees, so their compensation may also include bonuses, stock, retirement benefits, health insurance, and other benefits that are not included in the basic wage figure.
Data Scientist Salary Per Month
If the national median salary of $120,230 is divided into 12 months, it comes to roughly $10,019 per month before taxes. This is a simple monthly calculation and does not mean every data scientist receives the same monthly paycheck.
| Salary Measure | Approximate Pay |
|---|---|
| Annual median salary | $120,230 |
| Monthly equivalent | About $10,019 |
| Hourly equivalent | About $57.80 |
Actual take-home pay will be lower after federal taxes, state taxes where applicable, Social Security, Medicare, insurance, retirement contributions, and other deductions. Some data scientists can also receive annual bonuses or stock compensation, which can make total compensation higher than the base salary.
Data Scientist Salary by State
Location has a major effect on data scientist salary in the United States. A data scientist working in Washington, California, Maryland, New Jersey, or Massachusetts can earn a much higher salary than someone working in a lower-paying state. However, higher salary does not always mean more money left after living expenses because housing and other costs can also be higher.
The table below uses the May 2025 median annual wage for Data Scientists by state. The figures are based on BLS Occupational Employment and Wage Statistics data. Washington has the highest median among the states at $163,350, followed by California at $141,590 and Maryland at $136,370.
| State | Salary Amount |
|---|---|
| Alabama | $103,120 |
| Alaska | $84,110 |
| Arizona | $107,240 |
| Arkansas | $109,390 |
| California | $141,590 |
| Colorado | $117,400 |
| Connecticut | $126,340 |
| Delaware | Data not separately reported |
| Florida | $115,820 |
| Georgia | $104,340 |
| Hawaii | $102,130 |
| Idaho | $89,380 |
| Illinois | $106,560 |
| Indiana | $91,470 |
| Iowa | $95,830 |
| Kansas | $98,130 |
| Kentucky | $91,760 |
| Louisiana | $78,760 |
| Maine | $90,880 |
| Maryland | $136,370 |
| Massachusetts | $131,750 |
| Michigan | $100,590 |
| Minnesota | $128,800 |
| Mississippi | $69,490 |
| Missouri | $97,090 |
| Montana | $100,490 |
| Nebraska | $98,230 |
| Nevada | $98,540 |
| New Hampshire | $100,620 |
| New Jersey | $135,280 |
| New Mexico | $95,850 |
| New York | $130,460 |
| North Carolina | $119,090 |
| North Dakota | $81,900 |
| Ohio | $102,630 |
| Oklahoma | $86,310 |
| Oregon | $125,990 |
| Pennsylvania | $106,850 |
| Rhode Island | $102,440 |
| South Carolina | $91,990 |
| South Dakota | $96,150 |
| Tennessee | $100,330 |
| Texas | $122,090 |
| Utah | $108,090 |
| Vermont | $127,070 |
| Virginia | $126,430 |
| Washington | $163,350 |
| West Virginia | $85,090 |
| Wisconsin | $106,680 |
| Wyoming | Data not separately reported |
Note: The state figures above are median annual wages from May 2025 BLS OEWS data. BLS does not publish a separate reliable estimate for every state and occupation combination, so suppressed or unavailable state estimates should not be replaced with a guessed number.
Highest Paying States for Data Scientists
Some states offer much higher data scientist salary than the national median. These areas usually have strong technology, finance, research, healthcare, and business markets where companies need professionals who can work with large amounts of data.
Washington currently has the highest median data scientist salary among states at $163,350 per year. California follows with $141,590, while Maryland, New Jersey, and Massachusetts also report median wages above $130,000.
- Washington: $163,350
- California: $141,590
- Maryland: $136,370
- New Jersey: $135,280
- Massachusetts: $131,750
- New York: $130,460
- Minnesota: $128,800
- Vermont: $127,070
- Virginia: $126,430
- Connecticut: $126,340
Washington and California are especially interesting for people researching high paying data scientist jobs. But salary should not be considered alone. A data scientist comparing jobs should also look at housing costs, taxes, commute, benefits, remote work options, and the type of company offering the position.
Lowest Paying States for Data Scientists
Data scientist salaries are not equally high across the country. Some states have a lower median wage because the local job market, employer mix, and demand for advanced technology workers can be different.
Mississippi has the lowest reported median salary in the 2025 state data at $69,490 per year. Louisiana follows at $78,760, while North Dakota and Alaska are also below $85,000.
- Mississippi: $69,490
- Louisiana: $78,760
- North Dakota: $81,900
- Alaska: $84,110
- West Virginia: $85,090
- Oklahoma: $86,310
- Idaho: $89,380
- Maine: $90,880
- Indiana: $91,470
- Kentucky: $91,760
A lower state median does not mean every data scientist in that state earns a low salary. Experienced professionals, people working for national companies, and workers with specialized skills can still earn well above the local median.
Data Scientist Starting Salary
The starting salary for a data scientist is normally lower than the national median because the median includes workers with different levels of experience. Entry-level data scientists may start closer to the lower part of the national wage distribution, while their salary can increase as they gain professional experience.
A person entering data science for the first time may work as a junior data scientist, data analyst, machine learning analyst, or in another related position before moving into more advanced data science jobs. The actual starting salary depends on education, programming skills, statistics knowledge, location, industry, and the employer.
- A bachelor's degree is commonly expected for entry into data science.
- Common degree fields include computer science, mathematics, statistics, engineering, and business.
- Python, SQL, statistics, machine learning, and data visualization can improve job opportunities.
- Internships and real-world projects can help candidates with limited professional experience.
- A master's or doctoral degree may be preferred for some specialized or research-focused positions.
Because of this, there is no single data scientist starting salary that applies to every new graduate. The local job market and the skills shown on the resume can make a noticeable difference.
Data Scientist Salary With Experience
Experience can make a big difference in data scientist salary. A person entering the field may start with a lower salary, but as they learn more about machine learning, statistics, programming, business analytics and large data systems, their earning potential can increase. There is no fixed salary for each year of experience because companies use different job titles and salary levels.
For example, a new data scientist may be hired as a junior data scientist, while someone with several years of experience may move into a senior data scientist or machine learning role. Experienced professionals may also become data science managers or lead important projects, which can increase total compensation.
- Entry-level data scientist: Usually starts below the national median salary.
- Mid-level data scientist: Can move closer to or above the national median as skills and experience increase.
- Senior data scientist: Often earns well above the national median, especially in technology and finance.
- Lead or principal data scientist: May receive a high base salary along with bonus and stock compensation.
- Data science manager: Can earn more because the position combines technical work with team and business responsibilities.
The national median wage of $120,230 is therefore not a starting salary. It represents the point where half of workers earn more and half earn less. The highest 10 percent of data scientists earned more than $199,130 in May 2025, showing how far compensation can rise for highly experienced professionals.
Senior Data Scientist Salary in the USA
A senior data scientist normally has several years of professional experience and is expected to handle more difficult problems than an entry-level worker. Senior professionals may design machine learning models, work with large datasets, guide junior employees, communicate with company leaders and help decide how data should be used in business.
Because senior data scientists are generally more experienced, their salary can be above the national data scientist median. However, there is no single official BLS salary number called "senior data scientist salary." The actual pay depends on the employer, location, industry and job responsibilities.
In large technology companies, financial institutions and other high-paying industries, senior data scientists may also receive bonuses, restricted stock, stock options or other compensation. This can make total annual compensation much higher than the basic salary shown in a job advertisement.
- Senior data scientists usually have stronger technical experience.
- Many work with machine learning and predictive modeling.
- Some lead projects or mentor junior data scientists.
- Strong business communication can increase career opportunities.
- Specialized skills can help experienced workers compete for higher-paying positions.
Data Scientist Salary by Industry
Industry is another important factor when looking at data scientist pay. Data scientists work in technology, finance, insurance, healthcare, media, consulting and many other areas. The same person with similar technical skills can sometimes receive a different salary depending on the industry and employer.
According to BLS May 2025 data, data scientists working in publishing, broadcasting and content providers had a median annual wage of $142,240. Computer systems design and related services had a median of $132,380, while credit intermediation and related activities had a median of $129,490.
| Industry | Median Annual Salary |
|---|---|
| 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 |
These numbers show why industry should be considered when comparing data scientist salary offers. Technology and finance-related employers may have more need for advanced analytics and machine learning, while other organizations may have smaller data teams and different salary budgets.
Data Scientist Salary in Technology Companies
Technology is one of the most attractive industries for data scientists. Technology companies collect huge amounts of user, product, advertising and operational data, so they need professionals who can turn this information into useful decisions.
Data scientists in technology-related companies may work on recommendation systems, artificial intelligence, machine learning, customer behavior, search systems, advertising optimization and product analytics. Large companies can also offer additional compensation beyond base salary.
For this reason, people searching for data scientist salary in tech should look at total compensation instead of only the salary number. A job with a slightly lower base salary can sometimes have better bonuses, stock, retirement benefits or other advantages.
Data Scientist Salary in Finance
Financial companies use data science for risk analysis, fraud detection, customer analysis, credit decisions, trading research and forecasting. Because financial organizations depend heavily on data, skilled data scientists can find strong career opportunities in this industry.
Credit intermediation and related financial activities had a median data scientist wage of $129,490 in May 2025 according to BLS. This was above the overall national median for data scientists.
People with a combination of data science, statistics, programming and financial knowledge can be especially useful to financial employers. Some finance positions can also include performance bonuses, which can make total pay higher than the basic annual salary.
Data Scientist Salary Based on Education
Education is important for a data science career because the work requires a strong understanding of mathematics, statistics, programming and analytical methods. BLS says data scientists typically need at least a bachelor's degree in mathematics, statistics, computer science or a related field. Some employers require or prefer a master's or doctoral degree.
A bachelor's degree can be enough for many entry-level data scientist positions, but advanced education may be useful for specialized roles. A master's degree can help candidates develop deeper knowledge of machine learning, statistics or artificial intelligence, while doctoral education may be more relevant for research-focused positions.
- Bachelor's degree: Common starting education for data science jobs.
- Master's degree: Can be useful for advanced analytics, machine learning and specialized positions.
- Doctoral degree: More common in research-heavy or highly specialized work.
- Certifications: Can demonstrate knowledge but normally do not replace strong technical skills and practical experience.
- Projects: A strong portfolio can help show what a candidate can actually build and analyze.
Education alone does not guarantee a high data scientist salary. Employers also look at programming ability, analytical thinking, communication, project experience and the ability to solve real business problems.
Skills That Can Increase Data Scientist Salary
Data science is a technical career, and employers usually want a combination of programming, statistics, machine learning and business skills. Learning one tool is not enough for most professional data science positions. The strongest candidates normally understand how different tools work together.
Python is one of the most useful programming languages for data science. SQL is also very important because many companies store business data in relational databases. Other useful technologies can include R, cloud platforms, machine learning frameworks and data visualization tools.
- Python
- SQL
- Statistics and probability
- Machine learning
- Data visualization
- Data cleaning and preparation
- Predictive modeling
- Artificial intelligence
- Cloud computing
- Business analytics
- Communication and presentation
Not every data scientist needs to be an expert in every technology. The right skill combination depends on the job. A machine learning-focused position can require deeper programming and modeling knowledge, while a business data science role may put more focus on analytics, experimentation and communication.
Data Scientist Salary and Machine Learning Skills
Machine learning is closely connected with modern data science. Companies use machine learning to predict customer behavior, detect fraud, automate decisions, recommend products and identify patterns in large datasets.
A data scientist who understands machine learning can qualify for roles involving predictive models, classification, recommendation systems and other advanced analytics work. However, machine learning should not be considered a shortcut to a high salary. Strong statistics, programming and problem-solving skills are still important.
As artificial intelligence continues to become part of business operations, professionals who can connect machine learning models with real business problems may have more opportunities. The salary will still depend on the position, company, experience and location.
How Much Does a Data Scientist Make in a Year?
According to the latest BLS data, the median data scientist salary in the United States was $120,230 per year in May 2025. The salary range is wide, with the lowest 10 percent earning less than $67,240 and the highest 10 percent earning more than $199,130.
This means the answer to "how much does a data scientist make" depends heavily on where the person is in their career. A beginner may earn much less than the national median, while an experienced professional in a high-paying market can earn well above it.
Location also matters. Washington reported the highest state median in the 2025 data at $163,350, while California reported $141,590. This is one reason salary by state is useful when comparing data science career opportunities.
How Much Does a Data Scientist Make Per Hour?
Using the national median annual wage, a data scientist earns the equivalent of about $57.80 per hour. This is a simple annual-to-hourly conversion and should not be confused with the exact hourly pay of every worker.
The BLS national OEWS data also reports a median hourly wage of $57.80 for data scientists in May 2025. The mean annual wage was $126,800, showing the difference between average and median salary measures.
When comparing job offers, it is better to look at the complete compensation package. Salary, bonus, stock, health insurance, retirement benefits, paid leave and remote work can all affect the real value of a job.
Data Scientist Job Outlook in the USA
The job outlook for data scientists is especially strong compared with many other occupations. The U.S. Bureau of Labor Statistics projects employment of data scientists to grow 35 percent from 2025 to 2035. That is much faster than the average for all occupations.
BLS projects about 24,800 openings for data scientists each year on average over the decade. Some openings will come from new jobs, while others will happen when existing workers leave the occupation or move to different jobs.
This strong projected growth is one reason data science remains an attractive career for people interested in technology, statistics, artificial intelligence and business analytics.
- Projected employment growth: 35% from 2025 to 2035
- Average projected openings each year: about 24,800
- Employment in 2025: about 275,600 jobs
- Growth is much faster than the average for all occupations.
The growth is connected to the increasing amount of data being collected by businesses and organizations. Companies need people who can analyze data, build models and help decision-makers understand what the numbers are showing.
Is Data Scientist a Good Career in the USA?
For people who enjoy technology, mathematics, statistics and problem solving, data science can be a strong career choice. The national median salary is above $120,000, and the occupation is projected to grow much faster than average through 2035.
But data science is not an easy career just because the salary is high. The job requires continuous learning because tools and technology keep changing. A person entering the field should be comfortable with numbers, programming and working with large amounts of information.
- High national median salary
- Strong projected job growth
- Opportunities across many industries
- Possibility of remote and hybrid work in some companies
- Career paths into machine learning and artificial intelligence
- Opportunities to move into senior and management positions
Data Scientist Career Growth
Data science offers several possible career paths. A person does not have to remain in exactly the same role throughout their career. With experience, a data scientist may move toward technical leadership, machine learning, management, analytics or specialized research.
A common career path can start with an entry-level data science position and later move toward senior data scientist, lead data scientist, principal data scientist or data science manager. Some professionals move into machine learning engineering, artificial intelligence or business leadership roles.
The best career path depends on what the person enjoys. Someone who likes coding and model development may prefer a technical path, while someone who enjoys managing people and business decisions may eventually move into management.
Data Scientist Salary vs Data Analyst Salary
Data scientist and data analyst jobs are related, but they are not exactly the same. Data analysts often focus on reporting, dashboards, business questions and interpreting existing data. Data scientists usually work with more advanced statistical models, machine learning and predictive analysis.
Because of the additional technical and mathematical requirements, data scientist positions can have higher salary potential. However, data analyst can be a good entry point for people who want to build experience before moving into data science.
- Data Analyst: Often focuses on reporting, dashboards and business analysis.
- Data Scientist: Often works with statistics, predictive modeling and machine learning.
- Senior Data Scientist: Handles more complex problems and may lead technical projects.
- Data Science Manager: Combines data science knowledge with team and business management.
What Affects Data Scientist Salary?
There is no single factor that determines data scientist pay. Salary is usually the result of several things working together. A person with strong technical skills may still earn less than another professional if they work in a lower-paying location or industry.
- Years of professional experience
- Education level
- Programming and machine learning skills
- Industry
- State and city
- Company size
- Job responsibilities
- Management or leadership experience
- Specialized technical knowledge
- Bonus and stock compensation
For someone comparing data scientist jobs, looking only at the advertised base salary can therefore give an incomplete picture. Total compensation and local cost of living are also worth checking before accepting an offer.
Remote Data Scientist Salary in the USA
Remote data scientist jobs have become an important option for professionals who want to work from home or outside a traditional office. Data science is a computer-based career, so many tasks can be completed using a laptop, cloud platforms, databases and online communication tools. However, not every data scientist job is remote.
Remote data scientist salary can be similar to or higher than traditional office jobs, but it depends on the employer, experience, location and company salary policy. Some companies pay according to the employee's location, while others use a national salary range for remote workers.
Current job listings also show that remote data scientist positions can have a wide salary range. For example, some senior or lead remote positions are advertised with six-figure salary ranges. This shows why candidates should compare the complete job offer rather than assuming that every remote data scientist receives the same pay.
- Remote data science work can reduce commuting costs.
- Some employers offer fully remote positions.
- Other companies use hybrid work arrangements.
- Remote salary can depend on the employee's location.
- Senior remote data scientists may receive higher compensation.
Data Scientist Salary Negotiation
Salary negotiation can make a noticeable difference when accepting a data scientist job. Candidates should not only look at the first salary number offered by an employer. Data science compensation can include base salary, annual bonus, signing bonus, stock, retirement contributions, health insurance and paid time off.
A candidate with strong technical skills and relevant experience may have more room to negotiate than someone applying for their first job. It is also useful to research the salary range for the same job title in the specific city or state.
Before negotiating a data scientist salary, candidates should understand their market value and be ready to explain why they are asking for a particular number.
- Research the salary range for the position.
- Compare similar jobs in the same location.
- Highlight relevant professional experience.
- Show measurable results from previous projects.
- Mention specialized skills such as machine learning or AI.
- Consider the full compensation package, not only base salary.
It is usually better to have a professional conversation about compensation instead of simply demanding a higher number. Employers may not increase base salary, but they could have flexibility with bonuses, additional vacation, remote work or other benefits.
Data Scientist Benefits and Total Compensation
Base salary is only one part of what a data scientist can earn. Many full-time employees receive additional benefits from their employer. These benefits can have significant financial value over the course of a year.
Large technology companies and other high-paying employers may also provide bonuses and equity compensation. For some experienced employees, these additional payments can make total compensation much higher than the advertised base salary.
- Base annual salary
- Performance bonus
- Signing bonus
- Stock or equity compensation
- 401(k) or retirement contributions
- Health and dental insurance
- Paid vacation and holidays
- Remote or hybrid work options
- Professional training and education benefits
Because benefits are different from company to company, two jobs with the same base salary may have very different total values. A data scientist should therefore compare the complete compensation package before making a final decision.
How to Become a Data Scientist
Becoming a data scientist usually requires a combination of education, technical skills and practical experience. According to the U.S. Bureau of Labor Statistics, data scientists typically need at least a bachelor's degree in mathematics, statistics, computer science or a related field. Some employers prefer or require a master's or doctoral degree.
There is no single degree that every data scientist must have. People enter the profession from different educational backgrounds, but strong mathematics, statistics and computer skills are important.
Step 1: Get the Right Education
A bachelor's degree can provide the foundation needed for an entry-level data science career. Common fields include computer science, statistics, mathematics, data science, engineering and related subjects.
Step 2: Learn Programming
Programming is an important part of modern data science. Python is widely used for data analysis and machine learning, while SQL is important for working with databases. Learning these tools can help a candidate work with real company data.
Step 3: Learn Statistics and Mathematics
Data science is not only about writing code. Professionals need to understand statistics, probability, distributions, testing, regression and other mathematical concepts to correctly interpret data and build useful models.
Step 4: Build Real Projects
A portfolio can help a new data scientist show practical ability. Instead of only listing courses on a resume, candidates can build projects using public datasets and explain the problem, method, results and conclusions.
Step 5: Apply for Data Jobs
Some people start directly in data science, while others begin as data analysts, business analysts or related technology professionals. After gaining experience, they can move into more advanced data science positions.
Best Degree for a Data Scientist Career
There is no single "best" degree for every data scientist. Computer science can be useful for people who want a strong programming and technology background. Statistics and mathematics can be useful for people who enjoy modeling and analytical work. Data science programs can combine several of these subjects.
- Computer Science
- Data Science
- Statistics
- Mathematics
- Applied Mathematics
- Computer Engineering
- Electrical Engineering
- Economics and quantitative fields
The degree becomes more valuable when it is supported by practical skills. A candidate who understands statistics but cannot work with real datasets may still struggle in a technical interview. The same is true for someone who can write code but does not understand how to interpret statistical results.
Data Scientist Certifications
Certifications can be useful for learning specific technologies, especially for people changing careers or adding a new skill to an existing technical background. However, a certification by itself does not guarantee a high data scientist salary.
Employers normally care about whether a candidate can solve real problems. A portfolio, professional experience, education and technical interview performance can be more important than collecting many certificates.
Certifications can still be helpful when they support a clear career plan. For example, a person interested in cloud-based data science may choose training related to a major cloud platform. Someone focused on machine learning may choose a certification or course that develops practical model-building skills.
Data Scientist Skills for Higher Paying Jobs
People who want to increase their data scientist salary should focus on skills that are useful in real business environments. Technology changes quickly, so learning should continue even after getting the first job.
- Advanced Python programming
- SQL and database management
- Machine learning
- Deep learning
- Statistics
- Natural language processing
- Data engineering concepts
- Cloud computing
- Generative AI
- Data visualization
- A/B testing and experimentation
- Business communication
Not every skill is required for every position. A good approach is to first learn the fundamentals and then specialize based on the type of data science job a person wants.
Data Scientist Salary and Artificial Intelligence
Artificial intelligence is changing the data science job market. Businesses are using AI systems to analyze information, automate tasks, develop products and make decisions. This does not mean that data scientists are becoming unnecessary. In many cases, companies need skilled professionals who can prepare data, build models, evaluate results and understand whether an AI system is actually solving the business problem.
The latest BLS projections specifically say that firms are expected to continue integrating AI-based systems into their workflows. Data scientists are expected to help businesses use AI and other technologies, improve business processes, make informed decisions and develop products.
This can create opportunities for data scientists who understand both traditional statistics and newer AI technologies. Professionals who keep learning may be better positioned as the technology changes.
Data Scientist Salary Compared With Other Technology Jobs
Data scientist salary is competitive with many other professional technology and mathematics occupations. However, salary should not be the only reason to choose this career. Different technology jobs require different types of skills and daily work.
| Career | 2025 Median Annual Salary |
|---|---|
| Data Scientist | $120,230 |
| Computer and Information Research Scientist | $140,300 |
| Mathematician and Statistician | $105,720 |
| Operations Research Analyst | $88,940 |
The table shows why it is useful to compare related careers before choosing a field. The required education, type of work, job availability and career path can be very different even when the jobs all involve computers, mathematics or data.
Does Data Scientist Salary Increase With Experience?
Yes, salary often increases as professionals gain experience, but there is no automatic salary increase every year. Moving to a higher-level position, changing companies, developing specialized skills or moving into management can have a larger effect than simply staying in the same role.
An experienced data scientist may take responsibility for important machine learning projects, mentor other employees or communicate directly with business leaders. These additional responsibilities can support higher compensation.
The national BLS wage distribution also shows a large difference between the lower and upper ends of the occupation. The lowest 10 percent earned less than $67,240, while the highest 10 percent earned more than $199,130 in May 2025.
Can a Data Scientist Make $200,000 a Year?
Yes, some data scientists can earn more than $200,000 per year, especially experienced professionals working in high-paying industries, locations or companies. BLS reports that the highest 10 percent of data scientists earned more than $199,130 in May 2025.
Some job offers can also include bonuses and stock compensation, which can push total annual compensation above $200,000. However, this should not be treated as the normal salary for every data scientist. The national median is $120,230, so a $200,000 salary is closer to the upper end of the occupation.
What Is the Highest Salary for a Data Scientist?
There is no fixed maximum salary for data scientists. The highest-paid professionals can earn substantially more than the national median through senior positions, leadership responsibilities, specialized skills, bonuses and equity.
BLS reports that the top 10 percent earned more than $199,130 in May 2025. Some private-sector job offers can advertise compensation above this amount, particularly for senior, lead or specialized positions. Actual pay depends on the employer and the complete compensation package.
Is Data Science Worth It in the USA?
For someone interested in mathematics, programming, analytics and artificial intelligence, data science can be a strong career option in the USA. The occupation has a high median salary and one of the fastest projected growth rates among major occupations.
BLS projects data scientist employment to grow 35 percent between 2025 and 2035, from about 275,600 jobs in 2025 to about 371,000 in 2035. Around 24,800 openings are projected each year on average.
Still, the career requires continuous learning. People entering this field should be ready to work with programming, statistics and changing technology. Those who enjoy solving problems with data may find strong long-term opportunities.
Final Thoughts on Data Scientist Salary in the USA
Data scientist salary in the USA remains strong, with a May 2025 median annual wage of $120,230. The career also offers a wide salary range, from less than $67,240 for the lowest-paid 10 percent to more than $199,130 for the highest-paid 10 percent.
Salary can change significantly based on state, experience, industry, education and technical skills. Washington, California, Maryland and other high-paying markets can offer much higher salaries, while some states have considerably lower median wages.
For someone planning a career in data science, salary is only one part of the decision. The strong 35 percent projected employment growth from 2025 to 2035, increasing use of artificial intelligence and continued demand for data-driven decisions make this a career worth considering for people with strong analytical and technical interests.
The best way to increase earning potential is to build real technical ability, gain professional experience and keep learning as data science and artificial intelligence continue to change.