Replit is used a lot in this context. Their agent is good, but their circumvent-policies-to-get-something-in-front-of-execs-quickly is an amazing and mis-priced feature.
Strats as a role has been downplayed and realigned a lot over the last several years. Traditionally, a strat was indeed a "quantitative strategist" that sat on the desk, often next to voice traders, developing tools, pricing models, trading systems, etc.
One of the people I regard as the Godfather/OG strat is Emanuel Derman (https://emanuelderman.com/). Another transformative (in my time) person in the Strat complex was Marty Chavez (https://www.rmartinchavez.com/). Both amazing people on and off the trading floor.
Goldman has done this for decades, pushing it even further by having developed their own language (Slang), graph db (SecDB), and IDE (SecView). Many engineers resist working it in, but for any strat it's mandatory.
If this and/or the policies, leadership, and mindset that enable these kinds of things interest you, I highly recommend Abundance by Ezra Klein and Derek Thompson. IIRC, they outline data centers in space in his utopian introduction.
What the "right answer" is will vary widely on application and analyst. That's one reason there are so many coordinate ref systems. If you keep everything in 3857, you'll get answers in ~meters, but whether that's "right" depends on where and how large the distance or geom is and what your precision threshold is. So, really, everyone's needs are necessarily "specific."
DuckDB > geopandas, certainly for anything out of core. Though, I recently gave up on importing 70GB worth of large multipolygons (from a csv in hex wkb), and just used a postgis container. In concert with DuckDB's growth, I'd also mark the advent of geoparquet.
The big change, in my view, over the past decade in GIS software, is in compute and storage efficiency across the typical stack. DuckDB has become a part of this, but h/t to the advances from shapely, geopandas, geoparquet, and GDAL. There's a lot of overlap in that venn diagram, and credit should be spread around. QGIS is great, too, though I feel there is market opportunity to apply 90/10 to its massive feature set and move it to the web.
Many criminal records, petty or otherwise, are public record. When archived, expunged or dismissed infractions never truly become that. A traffic violation or other petty misdemeanor from 20 years ago, that has been expunged from official record, can show up on a background check because companies archive public data. So, there is a flip side to this.
The UK still has a heavily embedded caste or caste-like social circumstance. Pharma and finance have somewhat eschewed this tradition, but even those industries still have its embedded lords and ladies. Many of their smartest head to the US (or elsewhere), and Brexit has set them back decades from achieving the "richest country" status. A software engineer can double their earnings by moving to the US (if they can manage to). The owners of capital are generally not creators, and until that changes nor will their economic station.
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Would be interested to also know how they handle per-title audio. With stereo -> 5.1 -> 7.1 and the sides and wide layout variants, how do they think about this during the inspection and encoding process? Being completely naive to Netflix's source media, and assuming it comes in a variety for formats and media, it seems like there are decision to make there. Though audio obviously has a much lower bandwidth burden, one would think there could still be QoE gains (and bandwidth savings) by doing things that AV1 can do with different scenes in something like OPUS.
You have two random uniform variables and the distance/difference/change between to finite points.
Put another way (and code it up if you want). Select two random uniformly distributed points between 0 and 1. Do this 10_000 times, whats the average distance between the two?
This gets to the question of "most probable" vs "expected value". A conversation I always welcomed.
Early in my career, when I first started interviewing, I used to ask a version of this to recent grads. It was never a make-or-break question, but I found it to be a great way to a.) see how people approach problem solving and probability and b.) see how they respond when you start asking whys (even if they answered/guessed 1/3). It's something that takes zero code to answer, and the intuition is easy to grok once explained.
The other part I particularly enjoyed was the people who initially guessed wrong, but then got to the answer intuitively almost always sent me code proving the answer.
For the record, my question was: "Two points are randomly and uniformly selected on a line 0.0 to 1.0. What is the most probable distance between the two points?"