Salary ranges are often the first thing people consider when researching a new career. Identifying the market value of a position allows you to validate if learning the skills are worth it. For the lucrative career path of data science, the average data scientist salary is more than worth the time it takes to learn foundational and advanced skills.

While the average data scientist salary depends on where you are in the U.S., the data shows that this field is well-paid no matter where you reside. If you are looking to make a career switch into data science that includes a move or if you’re curious about the average salary of your home state, we have what you’re looking for.

We gathered data on data science average salary and cost of living index to rank the states that pay the most. Two things to remember are that the cost of living rises and falls each year, and quality of life can vary.

What are Data Scientists making in 2020?

Nationwide, data scientists earn between $92k - $138k. As of Apr 3, 2020, the average annual pay for a Data Scientist in the United States is $119,130 a year. It’s no wonder that data science careers have exploded recently.

The top 5 states where the annual adjusted gross income is highest include:

The bottom 5 states where the annual adjusted gross income is lowest are:

Two big tech hubs, Colorado and California, have average data scientist salaries that landed them in the #10 and #11 spots respectively.


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Rank

State

Avg Data Scientist Income

Cost of living index

1

New York

$71,127

139.1

2

Massachusetts

$70,453

131.6

3

Washington

$69,961

110.7

4

D.C.

$69,942

152.1

5

Alaska

$69,328

129.9

6

New Hampshire

$67,752

109.7

7

Hawaii

$67,692

192.9

8

Connecticut

$67,076

127.7

9

New Jersey

$67,066

125.1

10

Colorado

$66,603

105.6

11

California

$65,973

151.7

12

Maryland

$65,265

129.7

13

Minnesota

$65,177

101.6

14

Georgia

$64,972

89.2

15

Iowa

$64,823

90.1

16

Rhode Island

$64,798

119.4

17

Montana

$64,736

106.9

18

Oregon

$64,723

134.2

19

Vermont

$64,350

114.5

20

Delaware

$64,173

108.1

21

New Mexico

$63,833

87.5

22

North Dakota

$63,540

98.9

23

Virginia

$63,459

100.7

24

Michigan

$63,401

88.9

25

Wisconsin

$63,254

97.3

26

Maine

$63,240

117.5

27

North Carolina

$63,233

94.9

28

Wyoming

$63,023

89.3

29

Tennessee

$63,006

88.7

30

Texas

$62,936

91.5

31

Ohio

$62,871

90.8

32

Kansas

$62,767

89

33

Mississippi

$62,691

86.1

34

Arizona

$62,387

97

35

Indiana

$62,134

90

36

Kentucky

$62,049

90.9

37

South Dakota

$62,029

99.8

38

Nevada

$61,835

108.5

39

Pennsylvania

$61,490

101.7

40

South Carolina

$61,003

95.9

41

Louisiana

$60,912

93.9

42

Nebraska

$60,044

90.8

43

Oklahoma

$59,586

87

44

Alabama

$59,534

89.3

45

Utah

$59,144

98.4

46

West Virginia

$58,726

91.1

47

Illinois

$58,571

89.3

48

Arkansas

$58,448

86.9

49

Idaho

$58,152

92.3

50

Florida

$57,449

97.9

51

Missouri

$47,526

87.1

The data used here for the national average data scientist salary data was taken from ZipRecruiter and Cost Of Living Index By State from the World Population Review.

Employment Opportunities

Average salary data indicates that data scientist job opportunities exist across the nation. Now more than ever, employers are looking for individuals with the ability to ask questions of large data sets, the skills to use the industry tools to analyze and present data, and the curiosity to continue looking for insights.

Working titles of graduates from data science include:

Data Science may sound like a career that can be done remotely, and for some positions this is true. Remote work culture has become more normalized and hiring employees from a whole different state is no longer an anomaly. In fact, if you haven’t looked at any remote data scientist positions so far, the range of options and caliber of companies hiring will pleasantly surprise you.

Data Science salaries after Thinkful

In a recent long-term outcomes analysis, a first in the industry, Thinkful Data Science graduates showed that before Thinkful, students were earning an average of $53k, and after Thinkful, jumped up to $77k in their first job. After just one year in the field, alumni were making an average of $101k. Check out our long-term student success outcomes for more information.

Making a change that lasts a lifetime

Thinkful’s data science program is offered in an accelerated full time, five-month format and a flexible part time, six-month format. Wondering what Data Scientists do on the day-to-day? Get all the in-depth details on how you can break into the industry, check out How to become a data scientist blog.

Data scientists come from all walks of life and the diverse backgrounds they come from only add to the unique insights they find. Python programming expert, Giles McMullen-Klein, went from medical physicist to financial journalist to radio host to data scientist and Python Programmer. That’s quite a professional journey--proof that you can be successful no matter what industry you transition from. Dive into Giles’s story and how he now has a widely popular YouTube channel dedicated to helping others learn Python.

Breaking into data science does require a strong foundation of mathematical skills, critical thinking abilities, and programming know-how. Since 2012, Thinkful has been teaching students tech skills to get into the industry and we know a thing or two about what you will need in order to succeed as a data scientist.

Four Skills You Need to Become a Data Scientist include:

1. Problem-solving intuition

The ability to look at a problem and strategize solutions is essential to be a successful data scientist. As a practicing data scientist, you don't just need to know how to solve a problem that's defined for you, but also how to find and define those problems in the first place. Oftentimes, data scientists don’t look at a problem and know exactly how to solve it. Establishing strong foundational skills helps instill confidence even when the solution seems distant.

2. Statistical knowledge

In the field, most data scientists are writing code and using functions and models. A mathematical and statistical foundation is important for understanding the underlying functions.
For example, understanding when variations in the data are statistically significant is critical to confirming assumptions and conclusions about insights.

3. Programming in an analytic language (R or Python)

A conceptual and practical understanding of programming languages is integral to operating successful on the job as a data scientist. Programming allows you to take vast amounts of data and process them quickly in a meaningful way. You’ll also be able to use programming to do things like scrape websites for data or use APIs. Right now some of the most popular languages for data science analytics include Python or R.

4. Curiosity (keep asking why)

Questioning data, sources, trends, models, and insights are at the core of data science. This thirst for knowledge keeps data scientists driven in the long run. Rarely is the first hypothesis supported and proved with statistical significance. Diving deeper into data and results allow for findings that may surprise you, or even change your whole view into the root of the problem.

To keep your curiosity working during your transition, research exercises like finding out the average data scientist salary and how to become a data scientist, all help you keep an inquisitive disposition. Giving yourself space for learning or projects outside of your day to day work is a great way to keep yourself curious and inspired.

Start the conversation

Researching a new career is half the battle. Now that you know how well-paid data scientists are, how intriguing and essential data science is, and the skills you’ll need to learn, let’s take the next step to launch your new career.

Thinkful is dedicated to helping you launch a successful tech career and we prove it through our advanced curriculum, one-on-one mentorship, dedicated career coaching and real-world portfolio.

Schedule a call with our admissions reps to have an introductory call at a time that works for you to get started. We will help you choose the right format and guide you through next steps to changing your career and becoming a highly paid data scientist. Our reps can also offer in-depth information on payment and financing options for the course that fits you best.


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