Louis G.

if that can save someone some time, "E13 TV-L 50%" = 50% of 54k/year brutto reference: https://oeffentlicher-dienst.info/c/t/rechner/tv-l/allg?id=tv-l-2024&g=E_13&s=1&zv=VBL&z=50&zulage=&stj=2024&stkl=1&r=0&zkf=0&pvk=0&kk=15.5%25

Hi Pete, I know this ad says full-time, but do you know if they're open to contractors by any chance?

Interesting and well written job ad. I read the role is for North America candidates. In case European candidates would be of interest I typically would be interested

By "tracking" I would mean the events that you can fire when a user interacts with an application, e.g. Google Analytics or other custom solutions. Let's take search as an example. You search for "US president", you get a carousel of president card at position zero, you click on the second one instead of the first one. This can fire a tracking event. You can then process that event to update semantic relatedness between word "president" and the president entities in your KG.

I know of a good one in one direction: if you come across a prefix but don't know what it is, you can enter it in prefix.cc :) found that super helpful. Would also be interested in any resource to go the other way

Agreed with Denise G.'s points. Like her, my comment will be more for generic data engineering rather than specific to data engineering for KGs. One thing I would add as far as data engineering goes is that you want to "go up the stack" as much as possible. By this I mean that getting your hands on the tracking is better than just doing the ETL. This could be done by your teammates or yourself but there is something great that happens when the people who know the downstream usecases are the ones designing the tracking: you can start tracking signals that would be otherwise ignored. Things like implicit human in the loop feedbacks. Once you have that, maybe that starts feeding your KG generation pipeline, or maybe you use it only for a simple chart on your KG+ML performance etc...