<p>Just as other folks have said, statistics is not math, and there are sufficiently many differences in how the two areas project to academia, the real life, and the SE system. My impression (based on limited excursions to math.SE) is that most questions on math.SE come from people who are studying math for their own enjoyment. The distribution of the question sophistication is bimodal: 90% of questions are graduate-level questions, and the remaining 10% of the questions are high school calculus.</p>

<p>Stats.SE sees visitors from computer science, economics, psychology, among others, so plenty of questions on stats.SE come from people who were thrown into statistics and had to produce a specific analysis for their report, dissertation or paper, with no intention of making statistics their lifetime passion and a career choice. They could be hit-and-run <code>user#######</code> folks who bring the discussion forum expectations into their formatting of the questions and answers, use of tags, etc. The level of sophistication of these questions is essentially "What does it mean to compute $\int_0^\infty x^2 {\rm e}^{-x} \, {\rm d}x$ by parts?", and there's a fair amount of noise because the different disciplines that use statistics (or machine learning, or feature extraction, or data science, or quantitatve methodology, or whatever the equivalents of statistics are in the disciplines) use their own idiosyncratic names for the procedures that they need to produce. This is all to say that there is little room to <code>soft</code>en this site any further, and that's why the <code>career</code>-related tags see little demand. The distribution of sophistication is smoother on stats.SE, I think, but this may be an artifact of the fact that you need to have a college degree to begin with before anything statistical would come your way, so you would have a need to address stats.SE.</p>

<p>Finally, the communities may have developed some conventions of what they mean by <code>advice</code> or <code>soft-question</code>. We have some high popularity <code>advice</code>-type questions about statistical tools (<a href="https://stats.stackexchange.com/q/1595/5739">Python?</a>; <a href="https://stats.stackexchange.com/q/33780/5739">SAS vs. R?</a>; <a href="https://stats.stackexchange.com/q/7815/5739">skillset of a statistician</a>; etc.), which don't ask specific technical questions, but instead ask broader why or what-to-do types of questions. A smart reader thinking about building their career in statistics would gain a lot from reading these. I guess we just did not have in our conventions that such questions should be tagged <code>advice</code>.</p>
