It’s no secret that data scientists are in high demand, taking the no. 1 spot in Glassdoor’s Best Jobs in America list in 2016 and 2017, and boasting a median base salary of $110,000.
To shed light on this growing field, job search site Glassdoor released a report this week detailing the current landscape of data science jobs, and the skills needed to break into a career in this field.
Glassdoor researchers constructed a skills “dictionary” containing more than three dozen separate coding skills relevant to data science. They then searched job descriptions for the skills listed in each posting.
SEE: Job description: Data scientist (Tech Pro Research)
Here are the 10 most frequently mentioned skills in job postings for data science positions, and the percentage of job postings they are found in:
1. Python (72%)
2. R (64%)
3. SQL (51%)
4. Hadoop (39%)
5. Java (33%)
6. SAS (30%)
7. Spark (27%)
8. Matlab (20%)
9. Hive (17%)
10. Tableau (14%)
Nine out of every 10 job postings in the sample required at least Python, R, and/or SQL skills, Glassdoor found. These skills are closely interconnected, which makes them “bread and butter skills” that every data science job seeker should learn, according to the report.
“If you’re looking to enter the field of data science, and build a solid foundation of experience that will stand out in the eyes of future employers, there are three core skills you need: Python, R and SQL,” Pablo Ruiz Junco, Glassdoor economic research fellow, told TechRepublic. “With these skills, you’ll be eligible to apply to over 70 percent of all online job postings for data scientist roles. Plus, expanding your skills beyond these foundational languages can lead you to a higher salary and allow you to cast a wider net when applying.”
Python is the fastest-growing programming language in general, according to a report from Stack Overflow: By 2019, it will significantly outstrip other languages in terms of active developers. And data science is the factor driving Python’s sharp uptick in use, Stack Overflow found.
“Python is free, easy to learn and has a very large user base,” Ruiz Junco said. “Because of its large user base, many specialized packages for statistics, machine learning and graphing are available for data scientists to use. Plus, writing code in Python makes it more shareable within a company and easier to implement into production because it is so widely used by software engineers.”
To learn more about how to build a successful career as a data scientist, click here.