Capture Blog

Why Does Everyone Want To Be A Data Scientist?

Data and technology are at the core of everything Capture Higher Ed does. That’s why we often find ourselves explaining the relevance of data science as a field and the role of the data scientist as a crucial player for enrollment management.

Geoff Broome, an enrollment management solutions consultant for Capture, recently presented at the New Jersey Association for College Admission Counseling Annual Conference (NJACAC) where gave an overview of data science and its emerging role in higher education.

He started by pointing out that colleges in the United States have added 303 new accredited data science programs since 2010, an increase of 52 percent. Also, IBM and similar companies have partnered with more than 1,000 colleges to provide data science scholarships.

In fact, the Harvard Business Review recently named data scientist “the sexiest job in America” in 2016. An estimated 2,720,000 new jobs seeking data science and analytics will be posted in 2020.

So what is a data scientist again?

“A data scientist is someone who wants to look at a difficult problem, or ask a difficult question, like any scientist would, and then try and develop meaning or answers using quantitative data,” says Brad Weiner, director of data science at Capture.

The work of a data scientist involves using automated methods to analyze massive amounts of data and to extract knowledge from them. It also requires a multidisciplinary blend of data inference, algorithm development and technology to solve analytically complex problems.

One simple way to look at it: Data scientists tend to be better programmers than most statisticians, and better statisticians than most programmers.

data scientist

10 Things Data Scientists Do

  1. Ask good questions! What don’t we know? What do we know?
  2. Define and test hypothesis — run experiments.
  3. Scoop, scrap, sink and sample business relevant data
  4. Munge and wrestle data. Tame the data!
  5. Explore data, discover data, discover its unknowns.
  6. Model data, model algorithms.
  7. Understand data relationships.
  8. Tell the “machine” how to learn from data.
  9. Create data products that deliver actionable insight.
  10. Tell relevant business stories from the data.

Why are data scientists so important these days? Two words: Big Data.

data scientist

The use of big data is forcing everyone to change the way they collect, store, manage, analyze and visualize data. In fact, data is growing at 40 percent annually and is predicted to reach 44 zettabytes by 2020.

data scientist

Enter the data scientist.

A good metaphor would be to think of data as crude oil. Crude oil is pumped from the ground and shipped to the refinery where it becomes gasoline. In this case, the data scientist is the refinery. He or she takes the raw data … and refines it into information that can be used.

Today, data scientists are enabling so many of the cool features all around us — including machine learning, which through streaming services drives the entertainment in 51 percent of U.S. households according to Fortune magazine.

At Capture, we are putting data science and machine learning to work for the enrollment management industry.

Excerpted from a presentation to the New Jersey Association for College Admission Counseling Annual Conference (NJACAC) by Geoff Broome, Enrollment Management Solutions Consultant for Capture Higher Ed, on May 22.

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