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You are viewing ARCHIVED CONTENT released online between 1 April 2010 and 24 August 2018 or content that has been selectively archived and is no longer active. Content in this archive is NOT UPDATED, and links may not function.Extract from Excellent Article by Bernard Marr
Key Capabilities of a data scientist
The term “data scientist” can cover many roles across many industries and organizations from academia to finance or Government. Hanks leads a team of 12 to 15 members responsible for all of the analytics at Whitepages, and their skillsets and duties vary. However, he tells me, there are three key capabilities which every data scientist has to understand.
- You have to understand that data has meaning
Hanks makes the point that we often overlook the fact that data means something and that it is important to understand that meaning. We have to look beyond the numbers and understand what they stand for if we are to gain any valid insights from it. Hanks points out “It doesn’t have anything to do with algorithms or engineering or anything like that. Understanding data is really an art, and it’s really important.”
- You have to understand the problem that you need to solve, and how the data relates to that
Here is where you open your tool-kit to find the right analytics approaches and algorithms to work with your data. Hank talks about machine learning – which is very popular right now, but makes the point that there are hundreds of techniques to use data to solve problems – operations research, decision theory, game theory, control theory – which have all been around for a very long time. Hank says “Once you understand the data and you understand the problem you’re trying to solve, that’s when you can match the algorithm and get a meaningful solution.”
Read the complete article at Big Data Uncovered: What Does a Data Scientist Really Do?
