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data science, other

Types of Degrees data science, other Majors Are Earning

Students pursuing data science, other can earn degrees at several award levels.

Award Level	Graduates
Bachelor’s Degree	7
Master’s Degree	41

What data science, other Majors Need to Know

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

Knowledge Areas

This major prepares you for careers needing data science, other 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

The skill set built by a data science, other program reflects the day-to-day work of related occupations:

• Reading Comprehension — Importance 4.0 / 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

The cognitive and physical abilities most relevant to data science, other 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 4.5 / 7.
• Inductive Reasoning — Importance 3.9 / 5; level 4.3 / 7.
• Deductive Reasoning — Importance 3.9 / 5; level 4.4 / 7.

Common Job Activities

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

Activity	Frequency / Importance
Working with Computers	4.6 / 7
Getting Information	4.5 / 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, other professionals:

Tool / Software	Category	In-Demand
Microsoft Office software	Office suite software	✓
Microsoft PowerPoint	Presentation software	✓
Microsoft Excel	Spreadsheet software	✓
SAS	Analytical or scientific software	✓
IBM SPSS Statistics	Analytical or scientific software	✓
Microsoft Access	Data base user interface and query software	✓
R	Object or component oriented development software	✓
StataCorp Stata	Analytical or scientific software	✓
The MathWorks MATLAB	Analytical or scientific 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, other graduates include:

• Data Analyst
• Data Modeler
• Data Engineer
• Interior Design Teacher
• Interdisciplinary Professor
• Adjunct Instructor
• Lecturer
• Project Management Professor
• Survey Research Teacher
• Humanities Teacher
• Naval Science Teacher
• Packaging Professor
• Teacher
• Foreign Student Adviser Teacher
• Foreign Service Teacher

Education Typically Required

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

Education Level	Share of Workers
Bachelor’s degree	58.4%
Master’s degree	21.0%
Doctoral degree	4.1%
Associate’s degree (or other 2-year)	4.1%
Postsecondary certificate	3.1%
Some college courses	2.9%
Post-doctoral training	2.5%
Post-baccalaureate certificate	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, other?

Gender Distribution

This field has a relatively balanced gender distribution: 54.2% women and 45.8% men among data science, other graduates.

Gender	Graduates	Share
Women	26	54.2%
Men	22	45.8%

Racial-Ethnic Diversity

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

Race / Ethnicity	Graduates	Share
White	15	31.2%
Asian	4	8.3%
Hispanic or Latino	4	8.3%
Black or African American	8	16.7%
Two or More Races	2	4.2%
Race Unknown	3	6.2%
International Students	12	25.0%

^{See minority definition below.}

Online data science, other Programs

Distance learning are documented by IPEDS for data science, other. 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
Master’s	1	0

^{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
Data Science	30.70
Data Science, General	30.7001
Computational Science	30.3001
Data Analytics, General	30.7101
Data Analytics, Other	30.7199

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.