stefanba3

This resonates to me. In my last job we didn't plan our authZ story very well (or at all!). As our company experienced explosive growth, we ended up implementing something that I suspect is pretty common: AuthZ policy as data because we ended up representing it in a postgres db, and policy as code because we then had to write an "engine" to interpret that data. There were none of these emerging cloud authZ solutions, having one might have saved us a lot of time and grief!

First off, congrats! The problem I always run into with existing offerings, which as you mention all go through Plaid or Yodlee, is that there is never enough transaction history available for what I need. Typically, its only 3 months' worth at most.

There is some great advice here already, so I'll just add: From an ROI perspective, climbing the corporate ladder is actually very risky. You must invest a ton of time (years) and energy. Do things you may not want to do. Yet only a very few reach the top. Trying other things, like a side project, will yield success or failure a lot faster.

I can't tell from the description... does this come with a character builder?

A hiring manager friend at a Seattle unicorn once asked me to look over resumes. I didn't have a full grasp of how prevalent these "consultancies" are and was puzzled by all the jargon-filled, similar-looking resumes from people who were clearly working for "consultancies". Now I know, they were all looking for a ramp off! Some (many?) may even make great hires, but it' s hard to tease them out by looking at those resumes.

Can I also evaluate input against my OPA policies with this?

In my (very long) experience, companies routinely post for Sr. Engineer where they would gladly take a less experienced person they liked.

There are lots of smaller all-remote companies around, it sounds like it might be worth your time to at least explore some of those.

A model that just takes grades and degrees, which is most of the actual data the article presents, as inputs probably does not work. There are so many more attributes to consider: race, tenacity, resilience, etc.

As a hiring manager, I find talking in detail about work (school or industry) a candidate has done is a lot more illuminating than a coding problem. The trick is that it takes more preparation and focus from the interviewer because they need to know how to ask the right questions, they must know how to guide the conversation in real time, they must understand details about entire project in a few minutes, etc.

I've tried to adopt mm tools a few times over the years. To me the main problem is I end up spending too much time adding things I never use again. Maybe I am just doing it wrong?