Before you clip the outliers

A tail worth looking at rather than removing. salary_max_usd on data-job-postings tops out at 409,000 against a median of 131,000.

The max is 1.2× the 99th percentile and 4.0 standard deviations above the mean. The median is 131,000, so the top of this column lives in a different regime from the middle of it.

select *
from data_job_postings
order by salary_max_usd desc
limit 20;

Run that before deciding anything. There are three things an extreme value can be, and they need opposite treatment: a data error, a real but rare event, or a different population that got mixed into the same table. Only the first is safe to drop, and you cannot tell them apart from the summary statistics — you have to look at the rows.

A ratio this modest is consistent with an ordinary heavy tail — nothing anomalous, just a distribution that is not symmetric.

Clipping at the 99th percentile is a decision to discard your most interesting rows. Sometimes right. Never automatic, and never silent — if a number in a report was computed on clipped data, the report has to say so.