Data Scientist Salary:

If you are interested in a career as a Data Scientist, you might wonder how much the job typically pays. Data Scientist salary ranges vary according to experience, location, and industry, but the median annual salary far exceeds the average household income. The U.S. Bureau of Labor Statistics estimates the median salary for Data Scientists to be upwards of $130,000 annually as of 2021. That’s more than double the U.S. median salary.

While this median salary points to a promising and lucrative career, it is important to consider the factors that ultimately determine how much you will make. These factors include:

• Education
• Experience 
• Industry 
• Location
• Specialization

The following sections take a deeper look at how each of these factors impacts the salary you can earn as a Data Scientist.

What is a Data Scientist?

Data Scientists extract meaning from raw data to detect patterns and propose solutions that meet an organization’s needs, especially the needs to compete and grow. A Data Scientist’s responsibilities include finding valuable data from data sources, developing machine learning algorithms, improving data collection procedures, cleansing and validating data integrity to ensure accuracy, and detecting patterns and solutions based on data. Data Scientists build models based on data, create data visualizations that communicate patterns and findings to stakeholders, and automate collection processes. Because data plays a critical role in the success of any organization, Data Scientists can build careers in business, technology, finance, nonprofits, and many other industries. 

Those who wish to become a Data Scientist should develop the analytical, statistical, and programming skills needed to manage and interpret raw data. These skills include understanding statistics, machine learning, and reporting tools. Aspiring Data Scientists also benefit from understanding the programming languages R, SQL, Python, Java, and C++. 

Read more about what a Data Scientist does.

What Affects Your Pay as a Data Scientist

What affects your pay as a Data Scientist? Salaries for Data Scientists are determined based on education, experience, industry, location, and specialization. Learn more in the following sections about how these factors impact how much you can earn as a Data Scientist.

Education

Many people entering a data science profession have a four-year degree from an accredited university or college. They might also hold a graduate degree such as a Master’s or PhD. The most common undergraduate major for Data Scientists is computer science. Although many applicants will have a four-year degree, it is not always necessary to have such a degree or a degree in computer science. What matters most to recruiters and employers is an applicant’s skills, knowledge, and ability to do the work required of the position.

Alternatives to earning a four-year degree or graduate degree include earning a data science certificate that teaches necessary skills such as Python programming, machine learning, SQL, and other topics every Data Scientist should know. 

So how does your education impact pay? As a general rule, the higher your education, the higher your earnings, but because the average salary for a Data Scientist is so much higher than average, those with a four-year degree still easily earn upwards of $100,000 per year.

Experience

Another factor impacting pay is the amount and type of experience you have in data science. Entry-level positions may not require any previous experience, but to advance in a data science career, you must take on new challenges and build on your foundational skills. If an entry-level position does prefer some previous experience, this experience can include freelance as well as volunteer work in data science.

To track how your experience grows over time, it helps to periodically review your resume, even if you do not intend to search for a new job at present. Take note of the projects you lead and contribute to, improvements you make to an organization, skills you gain, and other valuable experiences by writing them down while they are fresh on your mind. This will make it much easier to tailor your resume in the future when you are ready to explore new opportunities.

You also don’t always need to look elsewhere to earn more money as your experience grows. Competitive organizations help employees to advance internally and increase salaries based on experience gained. For example, you can expect a pay increase of around $20,000 to $30,000 annually each time you advance to a higher level as a Data Scientist. Data Science Managers can make upwards of $150,000 and $200,000 annually depending on experience and other factors. 

Industry

Major corporations tend to offer more competitive pay than other organizations, and this can also vary depending on the industry the organization is part of. According to Glassdoor, companies that pay the most for Data Scientists include Meta (the parent company of Facebook and Instagram), Ascendum Solutions, IBM, Quora, Oracle, Google, Amazon, Expedia, and Microsoft.

While nonprofits and small startups may not pay as much as large corporations, they can offer opportunities for those looking to find an entry-level position that does not require previous experience. Some people also choose to work for organizations that closely align with their personal values as this gives them greater satisfaction in their work. 

Location

Location also impacts how much you can earn as a Data Scientist. While metropolitan areas tend to pay higher than other locations, the increased cost of living in such areas can quickly eat up the surplus money made. If you find a remote position, however, you may have the ability to take advantage of the competitive pay offered by big companies while living in a location with a lower cost of living.

According to U.S. News and World Report, the top five best-paying cities in the United States for Data Scientists are: 

• San Francisco, CA
• San Jose, CA
• New York, New York
• Durham, North Carolina
• Charlotte, North Carolina

Specialization

Data Scientists who have learned an in-demand specialized skill can be rewarded for their expertise.

A Data Scientist might choose to specialize in:

•  Data mining and statistical analysis: This is the process of analyzing data sets to extract valuable information and insights. This specialization requires the use of statistical analysis and predictive models to detect correlations, patterns, and trends that predict future outcomes, thus helping organizations to make informed decisions. 
• Database management and architecture: Data Scientists in this specialization work with stakeholders to structure data organization, including the digital framework.
• Machine learning engineering: This specialization involves the feeding of theoretical models to machine learning software to amplify the model to work on a greater scale.
• Business intelligence and strategy: The combined use of data analytics, data visualizations, and predictive modeling detect patterns in data. These patterns reveal the current state of an organization and inform future planning and decisions. 
• Data visualization: This specialization focuses on creating visual representations of data, such as charts and graphs. Data Scientists might create data visualizations using software like Tableau or the Python library Matplotlib.
• Operations data analysis: This process uses data to detect opportunities for an organization to improve its operations.
• Marketing data analysis: This measures the effectiveness of marketing campaigns and provides information for improved effectiveness.

Pay Range for Data Scientists

Data Scientist salaries range from around $90,000 per year to as high as $230,000. With such wide variance, pay depends on several factors. Those with one year or less of experience make an average of around $120,000 annually. Those with three to five years of experience make closer to $170,000 yearly. 

Highest-Earning Job Titles for Data Scientists

Some of the highest-earning job titles for Data Scientists include: 

• Senior Data Analyst -Tthis title indicates several years of experience in data science and analytics. Annual salaries range from around $90,000 to $120,000, with the average salary for this job title coming in at around $90,000.
• Machine Learning Engineer - The average salary for this title is around $130,000 annually with a pay range of $110,000 to $130,000. 
• Senior Data Modeler - The range for this position is from $100,000 to $130,000 with the average annual salary at around $120,000.
• Senior Statistical Programmer - The pay for this job title falls between $90,000 and $120,000 with the average annual salary just north of $100,000.
• Clinical Statistical Programmer

As these job titles suggest, senior positions tend to pay higher than others, proving the rule that more experience typically equates to higher pay. Those who rise to the top of the ranks within an organization, earning the title of “Director,” can also expect top earnings.

Learn the Skills to Become a Data Scientist at Noble Desktop

If you are looking to start a new career in data science, you might think the only way for you to become a Data Scientist is by enrolling in a four-year university or pursuing other costly and lengthy educational options. However, there are many alternative methods available to help you transition into a data science career, including data science bootcamps and certificate courses designed to help working professionals gain the skills needed to obtain an entry-level job as a Data Scientist. Exploring in-person and live online data science bootcamps and certificate programs can help you find the class that meets your career goals, budget, and schedule. The first step to finding the class that fits your needs is to understand the differences between in-person classes and live online classes. 

In-person data science classes meet in a traditional classroom setting at a physical location. In-person classes have the advantage of providing all necessary equipment, such as computers and software, and allowing students to network with local professionals such as your classmates and instructor. You also have the advantage of learning from an expert instructor face-to-face. The primary drawback to in-person courses is the extra time and money required to commute to the physical learning location. Live online data science classes offer many of the same benefits as in-person classes, including the ability to learn in real-time from an expert instructor. You can also collaborate with classmates, and you have the advantage of learning remotely. 

Noble Desktop offers several different in-person and live online data science classes that can help you start a career as a Data Scientist. The Python for Data Science Bootcamp teaches students foundational programming concepts and how to handle different data types, use conditional statements to control the flow of a program, use Scikit-Learn, Matplotlib, Numpy, Pandas, and other Python libraries and tools. Noble’s Data Science Certificate program and Data Analytics Certificate program provide a deep dive into the topics and skills essential to launching a career in data science or data analytics and offer one-on-one mentorship and job search assistance. All Noble Desktop classes provide students with hands-on experience, flexible financing options, setup assistance, a free retake, small class sizes, and real-time guidance from an expert instructor.

Learn more about Noble Desktop’s in-person and live online data science classes.

You can also learn more about data science careers and data science learning options with Noble’s free Data Science Learning Hub.

Key Takeaways

• The median salary for Data Scientists is around $130,000 annually
• Factors that affect how much you can make as a Data Scientist include your education, experience, industry, location, and specialization.
• Senior positions pay more than entry-level and mid-level positions, so the highest-earning job titles tend to include words like “Senior” and “Director.”

• You can receive comprehensive training to become a Data Scientist through an in-person or live online course with Noble Desktop.