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How much do Data Scientists make?

By Team Multiverse

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Contents

  1. What is a Data Scientist?
  2. Data science job outlook
  3. How much do Data Scientists make in 2022?
  4. Average Data Scientist salary by state
  5. Top highest-paying cities for Data Scientists
  6. Data science roles
  7. Highest-paid Data Scientists by job title
  8. Factors that influence how much Data Scientists make
  9. Is it hard to become a Data Scientist?
  10. What skills does a Data Scientist need?
  11. Become a Data Scientist with Multiverse

If you’re considering a career in data science, you’ve likely asked questions like: How much do Data Scientists make? What skills and training do I need to become one?

Data science is an attractive and promising career path. According to a Glassdoor 2022 report(opens new window), data science is the third-best career in America.

Companies increasingly rely on data and on Data Scientists to power technology and make better business decisions. As a result, the supply of Data Scientists hasn't matched the demand.

The average Data Scientist salary is on the higher end—even for entry-level positions. If you have years of work experience in the field, you can easily land a job with a six-figure salary.

If that all sounds appealing, data science may be the job for you. However, there are many other aspects to consider from salary to job outlook, and we’re covering them all below.

What is a Data Scientist?

A Data Scientist gathers, cleans, analyzes, and interprets data, but that’s not all. Especially in more senior roles, Data Scientists develop algorithms and models to improve data or forecast future outcomes.

Data Scientists may:

  • Identify business problems that could be solved with data and analytics
  • Collect massive amounts of data and transform it into a workable format
  • Spot data trends and patterns to help an organization's bottom line
  • Interpret the data collected and identify opportunities
  • Communicate and work with management, team members, IT personnel,  and stakeholders to steer the organization in the right direction

Data science job outlook

There is a gap between data science demand and supply. Furthermore, data science is among the fastest-growing job fields in technology.

According to the U.S Bureau of Labor Statistics, the demand for data science skills will grow by 36% from 2021 to 2031(opens new window), which is much faster than the average for all other occupations. The BLS also estimates that each year for the next year, there will be 13,500 open data science jobs.

How much do Data Scientists make in 2022?

The average salary for data scientists in the US is currently $117,000, according to Glassdoor.

The figures presented are often averages based on a broad set of data. It may not consider factors like:

  • Experience
  • Entry or senior-level positions
  • Location and cost of living
  • Job title
  • Education
  • Inflation
  • Industry

Average Data Scientist salary by state

Based on data from the BLS(opens new window), the average Data Scientist salary can significantly vary from one state to another. For instance, the average salary in the highest-paying state (Washington) is $69,540 higher than that in the lowest-paying state (West Virginia).

Data Scientist salary in Washington is $25,240 higher than the national average. Here are the top highest-paying states for Data Scientists.

Top highest-paying cities for Data Scientists

If you enjoy the hustle and grind of big cities, you'll find plenty of career opportunities as a Data Scientist.

Like states, salaries between cities can range greatly. Armed with the right salary data though, you can decide if you want to work in a specific city. Then, compare the cost of living to the salary to determine if it’s a good fit for you and your lifestyle.

These are the top-paying cities for Data Scientists in the US:

Data science roles

Although Data Scientist is a job title on its own, there are also variations that you should know. For instance, some Data Scientists may specialize in engineering. Often the terms Data Scientist and Data Analyst are used interchangeably. However, there are slight differences in the role, responsibilities, and pay.

Here are common job titles associated with data science and their salary expectations.

Data Scientist

How much do data scientists make? According to the BLS(opens new window), the national average annual salary is $108,660. However, the BLS data is not broken down into individual job titles.

For this, we looked at salary by job title pulled from thousands of Indeed job postings. Based on these figures, the average salary for Data Scientists in the United States is $144,961.

Keep in mind the cost of living and your location. The salary for the city or state you reside in is going to be a better reflection of your potential salary.

Data Analyst

Data Analysts are responsible for interpreting data and forming insights. Unlike Data Scientists, they don’t usually form their own research questions or develop advanced data models. The average salary for a Data Analyst is $71,459.

Data Engineer

Data Engineers have the combined skills of data analysis and software engineering. A Data Engineer may help build the systems and infrastructure to collect, maintain and analyze data.

Because Data Engineers work with data architecture, they learn SQL. Depending on the role, they may also need to know programming languages like Java, Python, and Scala. The average salary for Data Engineers in the US is $136,569.

Data Architect

Data Engineers and Data Architects are closely related and often confused. Although these roles work closely together, they focus on different aspects of data architecture.

Data Architects focus on the big-picture and strategy behind building and maintaining an organization’s data systems. They create the vision and Data Engineers build it. In the US, the average salary for a Data Architect is $89,993.

Highest-paid Data Scientists by job title

Factors that influence how much Data Scientists make

Besides the job title, your experience, skills, career path, and location play a significant role in how much you can earn.

Experience

As you gain more experience, you can earn a higher salary. For each year of experience, you can get at an extra $2,000 to $2,500 income on the low end. Managers also tend to make higher incomes than standard Data Scientists.

Career path

Like any job, your previous work experience can help you negotiate a higher salary. For example, if you worked at or apprenticed at a recognizable Fortune 500 company, you could leverage that experience.

Large tech companies offer higher-than-average salaries to stay competitive. For instance, top high-paying companies for Data Scientists include Google, Netflix, Airbnb, Pinterest, PayPal, Apple, and Microsoft.

Location

As mentioned earlier, income depends on location. Companies in states like Washington, California, and New York pay a higher salary, but they also have a high cost of living. However, if an employer offers remote work, you might make a California salary and live at least part or all of the year in a state with a lower cost of living. It depends on the employer and their requirements.

Is it hard to become a Data Scientist?

There are hundreds of resources online that can help you learn data science—without the high tuition that colleges charge. With online certification and programs like Multiverse’s Data Fellowship, it is easier than ever to learn data science.

Multiverse’s Data Fellowship is completely free and teaches you everything you need to know to become a Data Scientist.

That said, it’s not without challenges. Data science isn’t for everyone. It requires a combination of skills ranging from computer science and machine learning to communication and problem-solving.

What skills does a Data Scientist need?

If you want to become a Data Scientist, you should be interested in developing these skills in your career:

  • Knowledge of mathematics: Math, primarily statistics, plays a large role in data analysis.
  • Data visualization: You’ll use visual tools to present and interpret complex data in an easy-to-understand format.
  • Data cleanup and analysis: Data Scientists often clean up and organize data that they collect from various sources into a workable format that end users understand.
  • Programming: To specialize in data engineering, you’ll need to know various programming languages—SQL, Python, C/C++, Java, and more.
  • Machine learning: Data Scientists use machine learning to improve the quality of data and product offerings.
  • Communication: Although analysis is important, you’ll also need to be able to clearly communicate your findings to others in an organization.

There are various certifications that can help you establish your expertise in these skills. Alternatively, you can join a Multiverse apprenticeship program to gain the skills and on-the-job training for data science.

Become a Data Scientist with Multiverse

If you've decided data science is the right career path for you, Multiverse makes it easy to get started. Multiverse offers two data-focused programs: a Data Fellowship and a Data Literacy program.

The Data Literacy program focuses more on how to interpret data for business intelligence. It’s a better fit for those that want to make more strategic, data-driven decisions, but may not be pursuing a Data Scientist role.

On the other hand, the Data Fellowship is designed for Data Analysts that want to build a strong data science foundation. You’ll learn SQL, data visualization tools, database fundamentals, and more.

Team Multiverse

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