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data science

Types of Degrees data science Majors Are Earning

Students pursuing data science may pursue degrees at several award levels.

Award Level	Graduates
Certificate	8
Associate’s Degree	52
Bachelor’s Degree	2,486
Master’s Degree	5,132
Doctor’s Degree	31

What data science Majors Need to Know

Studies in data science build a specific mix of knowledge, skills, and abilities — derived from O*NET surveys of workers in occupations that data science graduates commonly enter.

Knowledge Areas

This major prepares you for careers needing data science emphasizes the following knowledge areas:

• Computers and Electronics — Importance 3.9 / 5; level 5.0 / 7.
• English Language — Importance 3.7 / 5; level 4.3 / 7.
• Mathematics — Importance 3.6 / 5; level 4.5 / 7.
• Customer and Personal Service — Importance 3.2 / 5; level 3.8 / 7.
• Administration and Management — Importance 3.0 / 5; level 3.7 / 7.

^{Importance is rated 1–5; level is 1–7. Source: ONET Online — weighted across related occupations.*}

Skills

Skills developed in a data science program reflects the day-to-day work of related occupations:

• Reading Comprehension — Importance 3.9 / 5; level 4.4 / 7.
• Critical Thinking — Importance 3.9 / 5; level 4.2 / 7.
• Active Listening — Importance 3.8 / 5; level 4.0 / 7.
• Speaking — Importance 3.8 / 5; level 4.0 / 7.
• Writing — Importance 3.7 / 5; level 4.1 / 7.

Abilities

Innate abilities most relevant to data science careers — again drawn from O*NET surveys of related occupations:

• Written Comprehension — Importance 4.0 / 5; level 4.4 / 7.
• Oral Comprehension — Importance 4.0 / 5; level 4.6 / 7.
• Oral Expression — Importance 3.9 / 5; level 4.4 / 7.
• Deductive Reasoning — Importance 3.9 / 5; level 4.4 / 7.
• Inductive Reasoning — Importance 3.9 / 5; level 4.2 / 7.

Common Job Activities

Day-to-day, data science graduates report doing:

Activity	Frequency / Importance
Working with Computers	4.6 / 7
Getting Information	4.4 / 7
Analyzing Data or Information	4.4 / 7
Processing Information	4.3 / 7
Communicating with Supervisors, Peers, or Subordinates	4.2 / 7
Making Decisions and Solving Problems	4.1 / 7
Organizing, Planning, and Prioritizing Work	4.1 / 7
Updating and Using Relevant Knowledge	4.0 / 7
Documenting/Recording Information	4.0 / 7
Identifying Objects, Actions, and Events	4.0 / 7

Technology Skills Used on the Job

Most frequently-cited tools used by data science professionals:

Tool / Software	Category	In-Demand
Microsoft Office software	Office suite software	✓
Microsoft Excel	Spreadsheet software	✓
Microsoft PowerPoint	Presentation software	✓
IBM SPSS Statistics	Analytical or scientific software	✓
SAS	Analytical or scientific software	✓
Microsoft Access	Data base user interface and query software	✓
StataCorp Stata	Analytical or scientific software	✓
The MathWorks MATLAB	Analytical or scientific software	✓
R	Object or component oriented development software	✓
Structured query language SQL	Data base user interface and query software	✓
Python	Object or component oriented development software	✓
Microsoft Word	Word processing software	✓

^{Source: ONET Online technology skills, weighted across related occupations.*}

Sample Job Titles

Real job postings for data science graduates include:

• Data Analyst
• Data Modeler
• Data Engineer
• Lecturer
• Labor Relations Teacher
• Science Teacher
• Industrial Arts Teacher
• Weight Control Lecturer
• Packaging Professor
• Medical Secretary Teacher
• Urban Planning Teacher
• Assistant Professor
• Flight Simulation Instructor
• College Teacher
• University Professor

Education Typically Required

Across the occupations open to data science graduates, the typical level of education actually held by current workers is distributed as:

Education Level	Share of Workers
Bachelor’s degree	59.0%
Master’s degree	20.5%
Associate’s degree (or other 2-year)	4.1%
Doctoral degree	3.9%
Postsecondary certificate	3.1%
Some college courses	3.0%
Post-baccalaureate certificate	2.4%
Post-doctoral training	2.4%
High school diploma or equivalent	1.6%
First professional degree	0.1%

^{Source: ONET Online education / training / experience requirements.*}

Who Is Earning a Degree in data science?

Gender Distribution

This field skews predominantly male, with men earning 62.5% of data science degrees.

Gender	Graduates	Share
Women	2,891	37.5%
Men	4,825	62.5%

Racial-Ethnic Diversity

At the national level, the racial-ethnic distribution of data science graduates is as follows:

Race / Ethnicity	Graduates	Share
White	2,453	31.8%
Asian	991	12.8%
Hispanic or Latino	478	6.2%
Black or African American	315	4.1%
American Indian / Alaska Native	11	0.1%
Native Hawaiian / Pacific Islander	3	0.0%
Two or More Races	177	2.3%
Race Unknown	286	3.7%
International Students	3,002	38.9%

^{See minority definition below.}

Online data science Programs

Online study is reported by IPEDS for data science. The table below shows how many graduates earned at least some of their coursework online (Distance-Ed Available) versus completing the entire program online (Distance-Ed Only).

Award Level	Distance-Ed Available	Distance-Ed Only
Associate’s	4	3
Bachelor’s	9	4
Master’s	40	16
Doctoral (Research)	1	2

^{Distance-Ed Only = degrees completed entirely online; Distance-Ed Available = degrees including at least some online coursework. Source: IPEDS Completions by Distance Education status.}

Related Programs

You may also be interested in these closely related fields of study:

Program	CIP Code
Multi Interdisciplinary Studies	30
Accounting and Computer Science	30.16
Anthrozoology	30.34
Behavioral Sciences	30.17
Biological and Physical Sciences	30.01
Biopsychology	30.10
Classical and Ancient Studies	30.22
Climate Science	30.35
Cognitive Science	30.25
Computational Science	30.30
Cultural Studies and Comparative Literature	30.36
Cultural Studies/Critical Theory and Analysis	30.26

References

The racial-ethnic minorities count is calculated by taking the total number of students and subtracting white students and international students. This number is then divided by the total number of students to obtain the racial-ethnic minorities percentage.

• College Factual
• National Center for Education Statistics (IPEDS)
• O*NET Online
• U.S. Bureau of Labor Statistics
• U.S. Department of Education College Scorecard

More about our data sources and methodologies.