Data Scientist Salary Guide: What to Expect in 2023

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.

What is a data scientist?

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

Benefit from a strong employment growth rate

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]. 

How much do data scientists make?

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.

Factors that can influence your data scientist salary

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.

Data scientist salary insights by location

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

Data scientist salary insights by industry

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].

How education affects a data scientist's salary

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.

How experience affects a data scientist's salary

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].

How to increase your data scientist salary

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

Building new skills as a data scientist

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

• Big data

• 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

Data Analysis and Visualization Foundations

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.

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Skills you'll build:

Data Science, Spreadsheet, Microsoft Excel, Data Analysis, Data Visualization (DataViz), Pivot Table, IBM Cognos Analytics, Dashboard

Enhancing your data scientist resume

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

• Microsoft Azure Data Scientist Associate (DP-100)

• Machine Learning Specialization - Stanford

• Data Science Foundations: Structures and Algorithms Specialization - University of Colorado Boulder

You can take the next step with Coursera

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.

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IBM Data Science

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.

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Average time: 5 month(s)

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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