How do you find processes that can be automated? I've often thought that there must be a ton of this stuff in various industries where programmers aren't typically embedded.
> Programming as a profession is only moderately interesting. It can be a good job, but you could make about the same money and be happier running a fast food joint. You're much better off using code as your secret weapon in another profession. People who can code in the world of technology companies are a dime a dozen and get no respect. People who can code in biology, medicine, government, sociology, physics, history, and mathematics are respected and can do amazing things to advance those disciplines.
In my limited experience, it's a mixed bag.
Good: you get special treatment/opportunities because of a unique skill set and increased visibility on the end results of what you do.
Bad: management doesn't really know what you do between software releases, you're paid the going rate for your industry while SWEs make far more, and in-house software quality standards might not be established/followed.
As a tangential bonus, I've accidentally converted my PhD research coworkers to strict git/markdown thanks mostly to typora (windows application). I showed one person what my work flow and version history look like for some internal documentation and now they do the same and convert to word/pdf as a last step. As far as I can tell, no one outside of the math/cs intersection has the patience for latex.
Source: in that boat.
Edit: In regards to market rates, that can be alleviated somewhat in follow up negotiations (6-12 months in or so). It's hard to convince someone what you're worth / what your value proposition is when they're not used to hiring software people. You need to demonstrate your business effect first, since they typically don't have a clear picture of it.
It's already a huge pain dealing with know-nothings inside of tech firms. Now imagine having to cater to know-less-than-nothings somewhere else.
But it's like math, if you know it well enough, you'll find ways to use it everywhere. If you don't, you won't. You have to be the type of person that likes to innovate. Its hard to sell to prospective employers, but its great for demonstrating value once you are with an organization. All of my previous employers fight over trying to get me back when I've found myself looking for work. ...Now I work for myself and make my own work and I've priced myself out of their offers, but that's not so bad.
I would be interested in thoughts from anyone with ML experience who has reviewed said course's materials?
Formally from school, I've only had 3 semesters of scientific programming in Fortran and a shitload of math. That and years and years of building models and massaging data in Excel.
Mostly I'm just really used to learning a new API/tool and applying it to new things.
A lot of the ML stuff hasn't been fancy ML, just basic things but applied in really clever and novel ways.
Granted I don't know anything about that business, a quick google search comes up with an article from 2015 saying running a McDonald's provides an average annual profit of $150k so it sounds about in the right ballpark range: https://www.mymoneyblog.com/mcdonalds-franchise-cost-vs-prof...
My source is from the McDonald’s franchise disclosure documents. The money blog mentioned in sibling comments claim it’s less.
Very possible I skimmed and may have read it incorrectly, accounting is not my thing. As I have now reached the maximum amount of effort I'm willing to put into a forum comment, I'm not going to dig any further. But if you can tease out better information, I'd be curious to know.
Average profit margin 26-28% Average gross sales 2.2 - 2.6M Average operating income before rent/tax: 570k - 716k
"The rent paid to McDonald’s will vary based upon sales and McDonald’s investment in land, site improvements, and building costs."
It looks like that rent paid to McD's home planet is somewhere in the neighborhood of 10% of that investment (yearly? I guess?) but it seems to average about 100k-150k.
1. you _won't_ be happier running a fast food joint - the work is gruelling, and it's so easy to go bust. And you won't bring home six figures
2a. people who _actually_ can code are scarce, even in the tech industry. Source: conducted over 300 interviews
2b. quite logically, your coding skill will be most appreciated and compensated at a Big Tech Co, not at a government department where they will be simply unable to see the difference
As a young person with an interest in software programming (currently studying chemical engineering but still write C code now and then), what do you look for when trying to find out people who can _actually_ code?
examples of simple things: DFS/BFS walks; simple Project Euler problems; or "write a simple game in terminal, maybe with some form of minimax search" (a bit harder), or maybe a parser for simple arithmetic expressions
There are tons of software "engineers" who try to escape fintech for FAANGs or even startups, coming from top tier firms like Goldman and McKinsey.
Likewise, bioinformatics generally pays a lot less than traditional SWE roles.
So what I have seen is the exact opposite in practice: people with minimum coding skills in other fields trying to jump into tech firms.
Any time, a piece of paper is passed around or when people enter data manually you can either automate or improve the process. People are prone to errors.
Right now, I am rewriting a mission critical application, some trivial changes will save hours a week and improve the integrity of the information. It is not as exciting as writing algorithms but it is nice to see an application written by you used by 200+ people.
Off the top of my mind:
https://sellercentral.amazon.com/forums/c/selling-on-amazon/... https://community.ebay.com/t5/Tools-Apps/bd-p/tools-apps-db
I know similar situations have to be all around us. The problem, as you say, is finding out about them.
- more than 10 documents per day on year average, e.g a bank will receive new annual reports only in some calendar months but in massive scale
- average number of pages or lines of text per document, the longer the document the more mistakes will be made by humans, as they don't have the time to read everything in detail
- average pay of the FTE who is able to understand and process the document manually should be higher than the average pay of all employees in the company, to make sure the documents encapsulate business value
It's not a fixed set of KPI but helps us to sort out too narrow use cases.
By we I refer to the team behind my startup Konfuzio:
Small payback : on your English home page under "Operation of the software" > "Information security", there's one too many sentences:
> We set the highest standards both when creating the software and when processing your data. Both when creating the software and when processing your data we set the highest standards.
(First one is better imho).