Information technology has advanced greatly. For a developing country like Malaysia, without many data scientists, how can we best manage our education system to train these highly specialized scientists?
Do you think that statisticians who are also versatile at handling data can also function as data scientists?
Data scientists seem to be a group of people who have specialised skills across a number of domains. (Eg see this clever info graphic: http://www.fico.com/landing/infographic/anatomy-of-a-data-scientist_en.html). So they need these primarily strong maths/stats/analytical skills, but also need to be able to contextualise their findings to the specific business area. That seems to require a deeper understanding of the data itself and how the data systems holding the data will influence results in relation to the business needs. So I think data scientists need maths/stats, informatics skills and also a strong understanding of the business itself. In some areas of industry I think it is easier to become a data scientist from stats/maths and informatics background, and learn about the particular industry through experience. But in some highly specialised industries such as healthcare, I think it is very difficult to have sufficient understanding of the business area without having some experience in the actual business first, eg being a nurse, health scientist or physician first. I think this makes learning to be a data scientist very difficult.
Also I suspect it might be uncommon for someone with the type of brain that is good at maths/stats and technology, to also be god at the communication skills required to contextualise the analytical results and create actionable insights from the data.
From an educational point of view I think this is an extremely difficult field as it cuts across several disparate domains of knowledge and I think it is best structured at post graduate level. However, I think the educational system needs to encourage mixing across disparate areas to stimulate innovative thinking. Mark Dodgson, (innovation researcher, author and corporate adviser) describes innovation as being "T-shaped" because it stretches across disciplines, and I think this has to be the basis of training as a data scientist, which is an innovative emerging scientific domain.
Data Scientist could be a mathematician or statistician or demographer with a knowledge of information technology. As a data scientist, knowledge of maths and statistics are highly needed to be able to understand analytical summary of the data.
Thanks Yusuff. On this RG platform, we can get good feedback, and opinion/s of the specialists in each field.
A data scientist should have excellent skills in Math and statistical analysis but he/she should also have good background in other disciplines ( medicine, genetics, agriculture, etc). In developed countries, there are plenty of experts in certain fields who are also well trained in statistical analysis. However, Miranda's question concerns developing countries and in this regard I agree with Susan where getting a statistician to acquire more knowledge and expertise in a particular domain or the other way (getting an expert in a particular domain to acquire expertise in statistical analysis and management of data) depends on the industry domain. I think that in many disciplines this issue could be solved by encouraging holders of first degrees in these disciplines to pursue Master and PhD degrees in statistics or where possible to follow joint programs (I myself did a PhD in Animal breeding and Genetics with Minor in Statistics)
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