What is a typical data scientist salary?

While there are a few factors that impact a data scientist salary, education and experience seem to have the biggest impact on how much you can earn as a data scientist.

Data science is frequently cited as one of the hottest careers today. Several industries recognize the importance of harnessing big data to improve decision making and data science salaries are increasing with that demand. For instance, SalaryExpert lists the average base salary for data scientists as $123,540. The competition for data science professionals increases with their skill and experience—like those with an advanced degree—making it a rewarding career choice.

How much can you make as a data scientist?

Industries from all business sectors need professionals who use complex data to inform business strategy. The 2021 Robert Half Technology Salary Guide lists data scientist as a “critical technology role” and according to SalaryExpert.com in November 2022, their salaries range from an $84,854 entry level salary to $149,815 for senior level professionals.

The good news for anyone in the field is that compensation should only increase in the future. The 2021 Robert Half Technology Salary Guide adds that “demand for data science skills is likely to remain high as businesses accelerate their digital transformation process in the post-COVID-19 recovery.” It is not surprising then that SalaryExpert projects a 16 percent increase to $149,728 for the average data scientist salary.

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Data science salary by job title

The data science profession includes many career paths with salaries increasing for candidates with more experience, skills and expertise. For example, here is list of job titles and impressive salaries from the 2021 Robert Half Technology Salary Guide .

Title25th percentile50th percentile75th percentile95th percentile
Big Data Engineer132,500166,500197,750226,500
AI Architect123,750148,000166,000194,750
Data Architect123,250145,500168,500199,250
Data Scientist109,000129,000156,000185,750
Data Modeler83,250104,750129,500175,000

Factors impacting data scientist salaries

Data scientist salaries vary depending on location, company, level of experience, and education. The cost of living varies according to location, and pay tends to be higher in areas with a higher cost of living. MoneyGeek.com has a calculator that will show the cost of living calculator for U.S. cities. The Bureau of Labor Statistics says that the following states have the highest annual mean salary:

  • New York
  • North Carolina
  • Maryland
  • New Hampshire
  • Washington

Data scientist salaries also vary by company. The following ten companies, according to Galavanize.com, have the highest average compensation for data scientists, adjusted for cost-of-living index.

  1. Oracle, $186,000
  2. Walmart, $218,000
  3. Nvidia, $222,000
  4. Airbnb, $228,000
  5. PayPal, $189,000
  6. Lyft, $200,000
  7. Cisco, $199,000
  8. Apple, $203,000
  9. Snowflake, $186,000
  10. Twitter, $187,000

The impact of education and experience

There is no question that education and experience significantly impact data science salaries. For instance, the 2021 Robert Half Technology Salary Guide breaks down the factors leading to compensation for data scientists to show that professionals with the most experience, skills and expertise should compete for the highest salaries.

Data science success requires mastering key skills and a strong educational background, often including an advanced degree. According to KDnuggets, a website on data science careers and other topics, says that:

“Data scientists are highly educated – 88% have at least a master’s degree and 46% have Ph.D.s – and while there are notable exceptions, a very strong educational background is usually required to develop the depth of knowledge necessary to be a data scientist.” 

Developing that expertise also means acquiring the programming languages and methods necessary for professional success. Therefore, it is important for data scientists to develop expertise in these skills:

  • Programming languages like R and Python
  • Math and Statistics – especially multivariate calculus and linear algebra
  • Machine Learning
  • Deep Learning
  • Data Visualization and Communication
  • Cloud Computing
  • Data Wrangling
  • Database Management

But there are also non-technical skills that lead to professional success. KDNuggets says that data scientist must also possess:

  • Business acumen – an understanding of your industry and the business problems you must solve.
  • Communication skills – you will need to communicate your findings to a non-technical team and also understand business needs in order to properly wrangle data.
  • Teamwork – data scientists work on a team and will collaborate with partners across their organization.

Pursuing a data science program that will help you acquire these industry-relevant skills and real-world experiences is critical to success in a data science career.

Next steps

Learn more

The School of Applied Computational Sciences offers two master’s degrees — M.S. Data Science and M.S. Biomedical Data Science — and a Ph.D Biomedical Data Science program. Explore these programs and see how they can launch your career.


Read about the skills and methodologies you will learn through our M.S. Data Science, M.S. Biomedical Data Science, and Ph.D. Biomedical Data Science courses.

Contact us

Do you have questions about our programs? Contact an enrollment advisor at sacsenrollment@mmc.edu.

Updated Feb. 1, 2023.

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