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Data Science in Virginia

Data Science Schools in Virginia

390 students earned Data Science degrees in Virginia in the 2022-2023 year.

As a degree choice, Data Science is the 229th most popular major in the state.

Education Levels of Data Science Majors in Virginia

Data Science majors in the state tend to have the following degree levels:

Education Level Number of Grads
Bachelor’s Degree 224
Master’s Degree 161
Post-Master’s Certificate 5
Postbaccalaureate Certificate 5

Gender Distribution

In Virginia, a data science major is more popular with men than with women.

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Racial Distribution

The racial distribution of data science majors in Virginia is as follows:

  • Asian: 18.2%
  • Black or African American: 4.9%
  • Hispanic or Latino: 3.1%
  • White: 41.8%
  • Non-Resident Alien: 13.1%
  • Other Races: 19.0%
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Jobs for Data Science Grads in Virginia

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Wages for Data Science Jobs in Virginia

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There are 2 colleges in Virginia that offer data science degrees. Learn about the most popular 2 below:

#1

William & Mary

Williamsburg
8 Degrees in Major Awarded
91% Graduation Rate
8,939 Total Students

The student to faculty ratio is 12 to 1. The average student takes 4.06 years to complete their degree at William & Mary. Students who attend this public school pay an average net price of $19,442.

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#2

Marymount University

Arlington
3 Degrees in Major Awarded
54% Graduation Rate
3,294 Total Students

Most students complete their degree in 4.23 years. An average student at Marymount will pay a net price of $23,659. Of all the students who attend this school, 98% get financial aid.

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Below are some popular majors in the state that are similar to data science.

Major Annual Graduates in VA
Other Interdisciplinary Studies 3,075
Biological & Physical Science 1,382
Peace Studies & Conflict Resolution 150
Science, Technology & Society 118
International Studies 102
Interdisciplinary Studies 66
Systems Theory 58
Mathematics & Computer Science 57

View all majors related to Data Science

View Nationwide Data Science Report

References

More about our data sources and methodologies.

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