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New Web App Uses Machine Learning To Analyze, Repair Your Technical Resume (techcrunch.com)
CV Compiler is a new web app that uses machine learning to analyze and repair your technical resume, "allowing you to shine to recruiters at Google, Yahoo and Facebook," reports TechCrunch. "The app essentially checks your resume and tells you what to fix and where to submit it," reports TechCrunch. "It's been completely bootstrapped thus far and they're working on new and improved machine learning algorithms while maintaining a library of common CV fixes." From the report: "There are lots of online resume analysis tools, but these services are too generic, meaning they can be used by multiple professionals and the results are poor and very general. After the feedback is received, users are often forced to buy some extra services," said Andrew Stetsenko. "In contrast, the CV Compiler is designed exclusively for tech professionals. The online review technology scans for keywords from the world of programming and how they are used in the resume, relative to the best practices in the industry."
The product was born out of Stetsenko's work at GlossaryTech, a Chrome extension that helps users understand tech terms. He used a great deal of natural language processing and keyword taxonomy in that product and, in turn, moved some of that to his CV service. "We found that many job applications were being rejected without even an interview, because of the resumes. Apparently, 10 seconds is long enough for a recruiter to eliminate many candidates," he said.
The product was born out of Stetsenko's work at GlossaryTech, a Chrome extension that helps users understand tech terms. He used a great deal of natural language processing and keyword taxonomy in that product and, in turn, moved some of that to his CV service. "We found that many job applications were being rejected without even an interview, because of the resumes. Apparently, 10 seconds is long enough for a recruiter to eliminate many candidates," he said.
Apparently, 10 seconds is long enough for a recruiter to eliminate many candidates
And therein lies the heart of the problem. In my experience, most HR depts are not that good at shortlisting candidates for tech positions, and some are downright terrible. Here's a tip: if you are hiring techies but you are not happy with the level of candidates HR sent you, ask them for all of the resumes that were submitted. You may be surprised at what you'll find there.
Maybe we ought to install this software at HR to clean resumes before they are read. Or perhaps replace the selection process entire with a machine learning system. (Although that comes with its own dangers, like hidden bias and spurious correlation).
If construction was anything like programming, an incorrectly fitted lock would bring down the entire building...
We shuffle the CVs, split the pile on two, and throw away half - they were the unlucky ones!
It is a technique I learned in MBA school!
Guys, before you go crazy fixing your CVs, do make sure you look at what permissions the app wants.
You need to register either by your Github - or your LinkedIn account. And it wants access to your private data, like e-mails, contacts, etc. Oh and it has your entire CV to boot - all that for a rather dubious benefit that any HR agency will do for you for free.
Don't be the product here.
if you know your thing, you can do it yourself therefore you don't need this privacy invasive service.
The problem with HR for tech companies, is that there is a LOT of money involved in the employment of tech people. So the industry, at all levels, from HR to recruiters, attracts shiny sales people who want to leech off the money fountain. It is exactly the same reason why there are no decent restaurants in popular tourist spots. All the legitimate restauranteurs get forced out by those with big promises and no moral integrity.
The whole tech HR landscape is a mess but I don't imagine it will get better until the bubble bursts and the money flows elsewhere.
Log in with your LinkedIn account, because job-hunting is what it's for, right?
The result included 7 "cards", only one of which actually referenced my resume. Two cards were advertisements for their paid service, while four were general suggestions (here's some keywords, a resume shouldn't be hard to read, etc.)
Only one page actually looked at my resume, and that reports how other resume review software might see your resume. This is the most useful service, since that software is the thing we're trying to work around.
So I found that positioning page and the keyword list useful. The rest is just fluff.
Here are the keywords they're excited about:
Not that this wasn't entirely predictable.