Must-Have Skills You Need to Become a Data Scientist

Here are  top data science skills that potential data scientists must have to be competitive in this growing marketplace. Every company will value skills and tools a bit differently, but if you have experience in these areas you will be making a strong case for yourself as a data science candidate. 


Technical Skills: Analytics 

·         Education – Data scientists are highly educated – 88% have at least a Master’s degree and 46% have PhDs – and while there are notable exceptions, a very strong educational background is usually required to develop the depth of knowledge necessary to be a data scientist. Their most common fields of study are Mathematics and Statistics (32%), followed by Computer Science (19%) and Engineering (16%).

·         SAS and/or R – In-depth knowledge of at least one of these analytical tools, for data science R is generally preferred. 

Technical Skills: Computer Science

·    Python Coding – Python is the most common coding language I typically see required in data science roles, along with Java, Perl, or C/C++.

·          b      ·  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.

Non-Technical Skills 

·         Intellectual curiosity – No doubt you’ve seen this phrase everywhere lately, especially as it relates to data scientists. 

·         Business acumen – 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.

·         Communication skills – Companies searching for a strong data scientist are looking for someone who can clearly and fluently translate their technical findings to a non-technical team, such as the Marketing or Sales departments. A data scientist must enable the business to make decisions by arming them with quantified insights, in addition to understanding the needs of their non-technical colleagues in order to wrangle the data appropriately.