Breaking down Data Science

The term “data science” first came around in 2001 for a field that’s been around for much longer. Fun fact, the term was coined by DJ Patil, former Chief Data Scientist of the U.S. Office of Science and Technology Policy and UCSD alum! In 2015, the role Data Scientist was ranked by Glassdoor as the number one job in America.

Data Scientists collect, manage, analyze and interpret large amounts of data with a wide range of applications. There are many roles or titles one can have in the data science field — from the more programming-heavy sides such as Data Engineer or Data Architect to the more statistical roles such as Data Analyst or Statistician.

Data Science is a fastly growing field with a diverse array of applications to many fields including business, healthcare, government, telecommunications, sports, and more.

These applications include advertising analytics, recommender systems, image and speech recognition, gaming, healthcare diagnostics, fraud detection, sports analytics, and much more.

Common technical skills among those in data science roles include computer programming (R, Python, SQL), math (statistics and probability), and machine learning.