Learn how your location, education, industry, and experience can play a role in how much you can earn as a data scientist.
In 2022, Glassdoor ranked data scientists as the third-best job in America [1]. If you enjoy analyzing data to identify patterns and solve problems, this career path holds plenty of well-paid opportunities for you. You can use this article to find out how much a data scientist makes and how you can increase your salary in this role.
Businesses generate massive amounts of data every day. This data includes everything from customer information to inventory tracking. Data scientists are tasked with managing this data and transforming it into actionable insight or, information companies can use to make critical decisions.
Read more: What Is a Data Scientist? Salary, Skills, and How to Become One
Between 2021 and 2031, the US Bureau of Labor Statistics estimates the employment rate for data scientists to grow by 21 percent by 2030 [2].
As of January 2023, the median salary in the US for data scientists is $125,053 per year [2]. This figure includes a base salary of $103,140 and a reported additional pay of $21,913 annually. Additional pay may include commissions, profit sharing, or bonuses.
According to Glassdoor, the lowest end of the pay range for data scientists is $78,000 per year. The highest end of this pay range is $204,000. Several factors can influence your salary as a data scientist in the United States. You can examine each one in the following few sections.
The data science field is well-suited for working from home thanks to its emphasis on independent work and technology. The average salary for a data scientist who works from home is $153,137 per year [3]. However, your location or your company's location can still influence your salary. The list below outlines five of the highest-paying cities in the US* for data scientists.
*All location-based salary insights were sourced from Indeed January 2023 [4].
1. Boston, MA - $170,758 per year
2. Los Angeles, CA - $165,887 per year
3. Houston, TX - $168,049 per year
4. Chicago, IL - $154,800 per year
5. Washington, DC - $147,169 per year
The industry you work in can play a significant role in your annual salary. For example, data scientists who work in real estate earn 18 percent higher salaries than those in other industries. The second highest-paying industry for data scientists is information technology (IT). IT data scientists earn 14 percent more than other industries [2].
Fifty-one percent of data scientists have a bachelor’s degree, 34 percent have a master’s degree, and 13 percent have a doctorate (PhD) [5]. Data scientists commonly study mathematics, statistics, business, or engineering. According to the Burtch Works Salary Report of 2022, data scientist salaries tend to increase with education level.
More experienced data scientists make more money per year on average. You can expect a salary increase as you ascend from an entry-level data scientist (Level 1) to a mid-level data scientist (Level 2), and so on. It's also important to note that data scientist manager roles (or, positions that require you to supervise others) pay more. The table below gives a breakdown of average data scientist salaries by experience [6].
Experience Level | Expected Salary | |||
---|---|---|---|---|
Data Scientist Level 1 | $90,000 | |||
Data Scientist Level 2 | $115,000 | |||
Data Scientist Level 3 | $145,000 | |||
Data Scientist Manager Level 1 | $155,000 | |||
Data Scientist Manager Level 2 | $200,000 | |||
Data Scientist Manager Level 3 | $275,000 |
As mentioned above, data scientist salaries typically increase with your education level. If you don't yet have a degree, consider earning a bachelor's or master's degree in data science or a related field. Some higher-paying senior data scientist roles may require a PhD. If you want to obtain an advanced role, consider earning an advanced degree.
Read more: Master's in Data Science: Your Guide
Degrees are just one of many ways to increase your salary. You can also obtain a higher salary by expanding your skill set. The list below outlines a few of the most important technical skills for data scientists to master:
Machine learning/deep learning
Artificial intelligence (AI)
Risk analysis
Cloud tools and data analysis platforms
Software engineering skills/programming languages
Statistical analysis
Data mining and cleaning
Data warehousing and structures
In addition to technical skills and knowledge, it's essential for data scientists to be good communicators. They must be able to report their findings in an easily digestible way so that non-data scientists can understand them. Communication skills are especially important for those pursuing a role in data science management. You can brush up on your data presentation and visualization skills by earning a certificate from IBM in Data Analysis and Visualization.
specialization
Get ahead w/ Data Analysis & Visualization skills. Enhance your career by learning to analyze data using Excel spreadsheets, and create stunning visualizations and interactive dashboards with Cognos.
4.8
(2,139 ratings)
11,792 already enrolled
BEGINNER level
Average time: 4 month(s)
Learn at your own pace
Skills you'll build:
Data Science, Spreadsheet, Microsoft Excel, Data Analysis, Data Visualization (DataViz), Pivot Table, IBM Cognos Analytics, Dashboard
Learning the skills above is the first step. The next step you'll need to take is to showcase those skills on your resume. One way to ensure your most in-demand skills stand out to employers is to earn a Professional Certificate in a relevant area of expertise. Professional Certificates on Coursera's platform are often provided by industry leaders and accredited universities such as IBM, Microsoft, Stanford University, and the University of Colorado Boulder. Check out this list of online courses that provide you with a data science certificate upon completion:
Data Science Fundamentals with Python and SQL Specialization - IBM
Business Intelligence Foundations with SQL, ETL, and Data Warehousing - IBM
Data Science Foundations: Structures and Algorithms Specialization - University of Colorado Boulder
To elevate your chances of becoming a highly paid data scientist, you should focus on advancing your education and gaining hands-on experience. You can get started today by enrolling online to earn an IBM Data Science Professional Certificate.
professional certificate
Kickstart your career in data science & ML. Build data science skills, learn Python & SQL, analyze & visualize data, build machine learning models. No degree or prior experience required.
4.6
(61,871 ratings)
172,612 already enrolled
BEGINNER level
Average time: 5 month(s)
Learn at your own pace
Skills you'll build:
Data Science, Deep Learning, Machine Learning, Big Data, Data Mining, Github, Python Programming, Jupyter notebooks, Rstudio, Methodology, CRISP-DM, Data Analysis, Pandas, Numpy, Cloud Databases, Relational Database Management System (RDBMS), SQL, Predictive Modelling, Data Visualization (DataViz), Model Selection, Dashboards and Charts, dash, Matplotlib, SciPy and scikit-learn, regression, classification, Hierarchical Clustering, Jupyter Notebook, Data Science Methodology, K-Means Clustering
Glassdoor. "50 Best Jobs in America for 2022, https://www.glassdoor.com/List/Best-Jobs-in-America-LST_KQ0,20.htm." Accessed January 3, 2023.
Glassdoor. "How much does a Data Scientist make? https://www.glassdoor.com/Salaries/data-scientist-salary-SRCH_KO0,14.htm." Accessed January 3, 2023.
ZipRecruiter. "Remote Data Scientist Salary, https://www.ziprecruiter.com/Salaries/Remote-DATA-Scientist-Salary." Accessed January 3, 2023.
Indeed. "Data Scientist Salary in United States, https://www.indeed.com/career/data-scientist/salaries." Accessed January 3, 2023.
Zippia. "Data Scientist Degrees and Education Requirements, https://www.zippia.com/data-scientist-jobs/education/." Accessed January 3, 2023.
Burtch Works. "The Burtch Works Salary Report - 2022 Edition, https://www.burtchworks.com/wp-content/uploads/2021/06/Burtch-Works-Study-DS_Analytics-2021.pdf." Accessed January 4, 2023.
This content has been made available for informational purposes only. Learners are advised to conduct additional research to ensure that courses and other credentials pursued meet their personal, professional, and financial goals.