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.
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.
Bloomberg did a similar thing decades ago, where they had their own database and their own take on TCP/IP. But this was done out of necessity since they started in the 80's and the database landscape looked very different than it does today.
They continued with their own db for decades out of inertia and also it worked fine. I think they've long since switched to TCP/IP and the public internet (for a time there was a Bloomberg network parallel to the public internet).
Yes, and our database, ComDb2, was open-sourced. It still powers the company today. And yes, we use TCP/IP :) And yes, we still have one of the largest private networks in the world.
I would never want to work for a place like Goldman anyway, but knowing they had their own idiosyncratic tech environment would certainly be an additional negative.
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.
it means "strategy". I imagine each "strategy" looks at some data and decides what kinds of trades to make in response, or predicts the price of some securities and sends that to a downstream process which decides what trades to make based on those price predictions.
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."
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