Often candidates for entry level data science positions find that they need to differentiate themselves is by having domain knowledge. Very rarely are employers looking to employ an entry level data science graduate for solving a general or a company wide problem. Most of the times employers are looking to solve a reasonably narrow set of issues or are looking for experience in a particular domain. While domain knowledge is not a substitute for experience, it can help a candidate gain extra skills or working with domain specific software tools. Understanding the nuances of the field and the requirements differentiates a candidate from other candidates with generalized data science knowledge and skill sets. The reason for is that companies hire data analysts or data scientist with prior experience with their “particular problem” and rarely hire all round generalist data science candidates.
