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Data scientist versus data analyst: confusion reigns

The data scientist position is often thought of as being the creation of the big data age, and distinct from the roles that went before it. In most organisations, and in the minds of many recruiters, the distinctions are not so clear, however. Not surprisingly, perhaps, given that data scientists can command a considerably higher salary, there has been plenty of surreptitious CV tweaking going on as analysts seek to manoeuvre themselves into the data scientist bracket.

In our previous research programmes Computing has found that a data scientist is more likely to be looking at what will happen, rather than what has happened. They will be more exploratory in their user of data and will go into more depth, experimenting to uncover correlations and trends for further analysis, or to come up with interesting new findings that no-one has thought of before. They also need a culture that brings them into daily contact with the business so that they do not become isolated and their projects irrelevant. 

While the analyst role is also changing in line with advances in analytics technology and the advent of more data centric business transformations, their role is generally still considered as move involved with historical data in a classic BI fashion.

However, our latest study in this area threw up a few surprises. Asked to choose the top attributes for data scientists and data analysts, respondents selected experience in real-time analytics second only to presentation skills. Real-time analytics is one of the fields that we would have thought to be firmly in the data science camp. Likewise, machine learning models, another data science staple, were high on the list for data analysts at number four, but way down on the data scientist priorities at number 15.  The top five for each role are shown below.

Data scientists

  • Able to extract insights from different types of data
  • Able to identify a problem and find a solution
  • Able to think creatively using data
  • Understanding the business
  • Delivering insights based on new data

Data analysts

  • Presentation skills
  • Experienced in real-time analytics
  • Able to work in multi-disciplinary teams/collaboration
  • Able to build a machine learning models
  • Understanding the business

In the later stages of our research we will be asking a number of CIOs to interpret these findings, in hope of enlightenment. It could be for example, that the respondents placed aptitude above skills and tools in their assessments – the top five attributes for data scientists certainly fall into this category.

For now though, these results have us scratching our heads. Whatever they mean, they are another sign that when it comes to the data analyst and data scientist roles – confusion reigns. 

Full results of the research will be presented at the Big Data IoT Summit in May (see below).


Computing Big Data and IoT Summit logo

Computing’s Big Data IoT Summit 2017 and the Big Data IoT Summit Awards are coming on 17 May 2017. 

Find out what construction giant Amey, Lloyds Banking Group, Financial Times and other big names are doing in big data and the Internet of Things. 

Attendance to the Summit is free to qualifying senior IT professionals and IT leaders, but places are strictly limited, so apply now. 

AND on the same day, Computing is also proud to present the Big Data IoT Summit Awards, too. See the finalists – and secure a table for your team at the Awards – now



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