<p>I'm relatively new to CV, and have very little history with SE, but as a practitioner with feet in both statistics and data science (you can put those in quotes if you want, I usually do since among practitioners both can be so broad you could have "statisticians" talking better about SQL than they do about MLE and "data scientists" rabid about Hadoop and clueless about a t-test). I talk with a lot of industry folks, I work in federal government and contract for private firms. I'm not an expert at anything, so this is just my opinion.</p>

<p>I think our role should be to try and moderate the divide that is happening between "traditional" statistics and "fast-paced" data science. It may be that in other areas, statisticians have angst that data scientists get their glory and give none back, and data scientists see statisticians as slow and inflexible, but we should not be perpetuating that myth. To the extent that we can be welcoming and cross-over, and I think we would be doing the entire field (to include statistics and data science) a huge favor that may not be recognized for a while. I recognize there are aspects of data science (managing Big Data) that do not belong at CV - but every analytical tool, even visualization stuff that is very basic analysis, should be addressed at CV. And we should be careful to not be overly condescending when a poster comes at us with limited theoretical knowledge but has a good handle on working with data - that is the type of person who could run from a statistician. </p>

<p>Just my newbie opinion.</p>
