Data science skills that potential data scientists must have to be competitive in this growing marketplace from the perspective of a recruiter. Some of them are more valuable to organizations with a need for strategic planning of their data-driven enterprises, and some are more valuable for organizations needing people who are willing to get their hands dirty with the nuts-and-bolts mechanics of data.
Business Skills – To be a data scientist you’ll need a solid understanding of the industry you’re working in, and know what business problems your company is trying to solve. In terms of data science, being able to discern which problems are important to solve for the business is critical, in addition to identifying new ways the business should be leveraging its data.
Python Coding – Python is the most common coding language I typically see required in data science roles, along with Java, Perl, or C/C++.
Hadoop Platform – Although this isn’t always a requirement, it is heavily preferred in many cases. Having experience with Hive or Pig is also a strong selling point. Familiarity with cloud tools such as Amazon S3 can also be beneficial.
SQL Database/Coding – Even though NoSQL and Hadoop have become a large component of data science, it is still expected that a candidate will be able to write and execute complex queries in SQL.
Unstructured data – It is critical that a data scientist be able to work with unstructured data, whether it is from social media, video feeds or audio.