Today’s Information Technology and business worlds are faced with an overabundance of data. Information is great, but more than overwhelming raw data is needed to help an organization make informed actionable decisions. For that, you need data science and its practitioners, data scientists.
Looking to kickstart your career in data science? Joining a data science bootcamp can be the perfect way to enter this high-demand field. But high demand for data scientists means there are plenty of potential employers. So which ones pay the best? This article shows where to find the best data scientist salary for your circumstances. We will also highlight the average data scientist salary and data scientist salaries broken down by experience level (e.g., entry-level data scientist, mid-level data scientist). Finally, we’ll examine how other essential factors, such as education, hands-on experience, and communication skills, can affect pay.
First, let’s define data science and determine what a data scientist is.
What is a Data Scientist?
Before we define data science, we should explain what data science is. Data science involves studying data to extract meaningful insights for better business decisions. It’s a multidisciplinary approach combining the practices and principles from statistics, mathematics, computer science, scientific methods, processes, algorithms, artificial intelligence, machine learning, and computer engineering to analyze vast amounts of data.
Consequently, data scientists are analytics professionals responsible for collecting, analyzing, and interpreting large data quantities to help drive an organization’s decision-making process and solve problems. Data scientists combine elements of traditional technical jobs, like computer programmers, mathematicians, statisticians, and scientists.
Specific responsibilities include:
- Identify the data analytics problems that provide the best opportunities for the organization to grow and evolve
- Collect vast sets of structured and unstructured data from many different sources
- Determine correct data sets and variables
- Staying current with the latest analytical techniques like machine learning, deep learning, and text analytics
- Write code using a variety of programming languages such as SAS, R, and Python
- Clean, validate, and analyze data to ensure accuracy, completeness, consistency, and uniformity
- Devise and apply algorithms and models to mine big data stores
- Identify patterns and trends using data analysis
- Discover solutions and opportunities by interpreting clean, validated data
- Collaborate with other IT professionals in the organization
- Communicating findings to stakeholders through data visualization and other methods.
How does a data scientist accomplish this impressive laundry list of responsibilities? They use these tools:
- Data preparation. Converting raw data into a different format to make it more easily consumed.
- Data visualization. Presenting data in a picture or graph format for easy analysis.
- Deep learning. A subsection of machine learning research that employs data to model complex abstractions.
- Machine learning. A branch of artificial intelligence (AI) based on automation and mathematical algorithms.
- Pattern recognition. A technology that recognizes data patterns and is often used interchangeably with machine learning.
- Text analytics. Examining unstructured data to derive critical business insights.
Now that we’ve established the parameters for data science and data scientists let’s get into our data scientist salary information.
Read More: What is Data Science? A Comprehensive Guide
What’s the Average Base Salary for Data Scientists in the United States?
According to Indeed.com, the median salary for data scientists in the United States is $124,963 annually. Furthermore, the salary range goes as low as $76,739 and as high as $202,612. Bear in mind these are average salaries and subject to variations based on several factors such as location and experience level. Fortunately, we’ll be exploring those variables next.
This figure doesn’t include extra perks such as profit sharing or additional pay courtesy of bonuses or similar payouts.
Also, don’t be surprised to see different average base salary figures reported by various employment sites (e.g., LinkedIn, ZipRecruiter, Indeed, Payscale, etc.). Fortunately, most salary figures fall into an approximate range, so if you check several sites, you can come up with a respectable realistic working average.
Now let’s see how an entry-level data scientist salary varies from the wages of more experienced people in the same field.
Data Scientist Salary in the United States Based on Experience
It stands to reason that the more years you have in a given profession, the higher your salary. When an organization hires you, they pay what amounts to rent for your years of experience, skillset, time, talents, and energy. So, the more you know, the more you can ask for, and work experience is a valuable teacher.
Let’s look at data scientist salaries in the U.S. based on how long you’ve been in the field. These figures come courtesy of Payscale.com.
- Entry-level Data Scientist Salary (Less than one year experience). $86,434 per year.
- Early Career Level Data Scientist Salary (1-4 years of experience). $97,392 per year.
- Mid-Career Level Data Scientist Salary (5-9 years of experience). $112,442 per year.
- Experienced Level Data Scientist Salary (10-19 years of experience). $124,841 per year.
- Senior Data Scientist Salary (20+ years of experience). $136,914 per year.
Salaries for Positions in Data Science-related Fields
There are positions out there that share an affinity for data science. Any of these jobs could become landing spots for the data scientist looking to branch out in the field and try something different. Salary figures courtesy of Indeed.com
- Data Analyst. $70,683 per year
- Machine Learning Engineer. $150,150 per year
- Data Engineer. $128,601 per year
- Software Engineer. $109,020 per year
- Research Scientist. $84,683 per year
- Statistician. $86,834 per year
What Are the Best-Paying Industries for Data Scientists?
According to Glassdoor.com, the following industries pay data scientists the best salaries.
- Real Estate. $169,134 per year. This figure is 16% higher than other industries.
- Information Technology. $165,871 per year. This figure is 14% higher than other industries.
- Personal Consumer Services. $150,275 per year. This figure is 6% higher than other industries.
- Agriculture. $148,646 per year. This figure is 5% higher than other industries.
- Financial Services. $145,020 per year. This figure is 2% higher than other industries.
Today’s Top Companies for Data Scientist Salaries
The following fifteen companies are the current best-paying organizations, based on Indeed.com’s findings. Remember that these are averages and subject to fluctuations depending on the applicant’s skill level and experience.
- Stitch Fix. $204,387 per year
- Comcentric. $182,321 per year
- Wayfair. $173,000 per year
- Lyft. $172,445 per year
- Airbnb. $171,013 per year
- Selby Jennings. $170,698 per year
- LinkedIn. $166,307 per year
- Twitter. $165,416 per year
- eBay. $159,860 per year
- Meta. $158,306 per yea
- Apple. $151,567 per year
- Capital One. $151,561 per year
- Cisco Systems. $146,796 per year
- Microsoft. $144,680 per year
- Lawrence Livermore National Laboratory. $144,039 per year
What Are the Highest Paying Cities for Data Scientists in the U.S.?
Here’s a list of the highest-paying cities for data scientists in the United States, as reported by Indeed.com.
- Palo Alto, CA. $156,923 per year
- San Francisco, CA. $139,757 per year
- Seattle, WA. $136,392 per year
- New York, NY. $135,824 per year
- Boston, MA. $135,691 per year
- Redmond, WA. $135,646 per year
- Austin, TX. $119,410 per year
- Chicago, IL. $118,499 per year
- Irvine, CA. $114,881 per year
Also Read: Top Data Scientist Skills You Must Have
How Can Data Scientists Increase Their Salaries?
There are several methods available to increase a typical data scientist salary. The first and easiest is just hanging in there at the position and gaining seniority and experience. However, results can vary based on the company, so this strategy should be supplemented with other methods mentioned here.
If you’re working as a data scientist without a degree (an impressive accomplishment), consider returning to school and getting that degree in data science or a related field.
Or you could look for a better-paying position at another company. For example, let’s say you began working as a data scientist at Random Corp in 2019. You’re doing a great job, and your $120,000 starting salary has increased by 2 percent over the last four years. So, you’re now making $129,890. Great! Then Random Corp hires a newbie to supplement the department and starts them at $135,000. Unfortunately, this new person has less experience than you and fewer skills. When you call out the company on this, Random Corp explains they need to offer better starting pay to “stay competitive with the current job market.” When you ask them to boost your data scientist salary to match industry standards, they claim budget limitations, but to show their appreciation for your hard work, they give you a free hat with the company logo.
Time to find another job.
Finally, and much less dramatically, you can boost your data scientist skills and make yourself more valuable to the organization. Here is a list of critical skills you can improve, typically via online learning resources such as certification courses and bootcamps. And hold that bootcamp thought; we’ll be addressing them later.
- Artificial Intelligence (AI)
- Big Data
- Cloud tools and data analysis platforms
- Data mining and cleaning
- Data warehousing and structures
- Machine learning/deep learning
- Risk analysis
- Software engineering skills/programming languages
- Statistical analysis
The Data Scientist Career Outlook
We mentioned that data scientists are in demand. But how about some specifics? According to the U.S. Bureau of Labor Statistics, data scientist employment is projected to grow 36 percent from 2021 to 2031. This growth figure is considerably faster than the average for all United States occupations.
In addition, approximately 13,500 data scientist openings are projected for each year of the decade. Many of these data scientist openings are expected to come from the need to replace professionals who migrate to different occupations or leave the labor force altogether, such as for retirement.
So yes, the data scientist outlook appears promising.
Do You Want to Master Data Science?
If you want to gain a better mastery of data science, whether for a career change or upskilling your current skill set, you must sign up for this excellent data science bootcamp. In collaboration with IBM, Caltech’s Center for Technology and Management Education (CTME) will turn you into a data science expert in just six short months.
You will learn to make data-driven decisions through this highly acclaimed bootcamp which provides a high-engagement learning experience that leverages Caltech’s renowned academic excellence and IBM’s famed industry prowess in the data science field. You will gain skills such as:
- Data Visualization
- Deep Learning
- Descriptive Statistics
- Ensemble Learning
- Exploratory Data Analysis
- Inferential Statistics
- Model Building and Fine Tuning
- Supervised and Unsupervised Learning
Your data science skills will be validated through six months of applied learning, including over 25 hands-on projects with integrated labs and capstone projects in three domains. After that, you will be ready to work on getting a better career.
So, don’t delay. Sign up for this bootcamp today, get empowered in the fast-growing field of data science, and best of all, start earning a high data scientist salary!