The Use of Data Analytics in Recruitment
March 11th, 2019
With so much data around, many companies are rushing to hire data scientists and as a recruiter, I have seen a rise in this hiring pattern. But what many companies don’t realise is a lot of the time the need they have is actually for a highly skilled data analyst, not a data scientist.
It’s understandable that a company may want to hire a data scientist, at the end of the day it did get named the sexiest job of the 21st century!
There can be a lot of crossover between the two roles, but there are differences which can make you realise a data scientist may not be the answer.
The differences fundamentally come down to the role each plays in the business.
While both will be analysing data and presenting results – a data scientist will be looking for something that cannot be easily seen and where a desired target is not set. This helps the business to look towards the future and enables better decision-making, as the data scientist presents the data to support this.
A data analyst looks at data that is already available, they look at historic data presenting new perspectives on otherwise ‘old’ data. They will present new ways to collect this data and how best to bridge data quality gaps.
If you have a massive amount of data that needs statistics and mathematical tools to be applied in order to extract knowledge and insight, then a data scientist is for you. They will be able to build statistical models that will make the decisions based on the information, and they will become the thought leader in your business for data.
If you have a specific data set that needs analysing and extracting, then you should hire a data analyst. A data analyst will be able to write queries within the data to help answer business questions and aid decisions. Generally, many companies need a highly skilled data analyst rather than a data scientist.
While there is a lot of crossover between the role of a data scientist and a data analyst making sure you hire the right person can be essential to your business. Both will add value once you make the right decision.
Have you had to make the decision between a data scientist and a data analyst? Which did you choose and why?