Page 71 - Special Topic Session (STS) - Volume 3

STS515 Steve MacFeely
Figure 2 – Skills and Competencies of a Data Scientist / Statistician

3. Required Competencies
Any discussion of future requirements should, I think, be broadened beyond
skills to include competencies. Statisticians, like any other professional will need
2
to continually update their skills over the lifetime of their career . What is less
likely to change over time are the basic characteristics or competencies
necessary to be a good statistician. Specifically, I would argue a statistician must
be creative, curious, critical, skeptical and resourceful (see Figure 2). These I think
are self-explanatory and don’t require any elaboration. Perhaps, less obvious, a
statistician should also be aware of the cultural and civic or political environment
in which they operate. It is very important that a statistician not only
understands the context in which previous indicators and statistics were
compiled, but also that they properly understand the environment in which they
operate. For example, when contemplating the use of big data, MacFeely [1]
notes that NSOs may be forced to confront issues before the law is clear or
cultural norms have been established. Given the importance of public trust for
an NSO it is essential that statisticians are sensitive to these issues and
understand what is acceptable by the public they serve. The challenge for
universities is how to nurture and develop competencies.

2 Outside the scope of this paper, but perhaps there is a market for universities beyond
preparation of early career statisticians to cater better for mid and senior career statisticians
too?
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