4 ms·

Hi folks! OP here + author of the NLP algorithms in the post. If you're hiring and want us to help you with filtering like this, we're definitely keen to pilot

by cl42 6y ago

Hi folks! OP here + author of the NLP algorithms in the post. If you're hiring and want us to help you with filtering like this, we're definitely keen to pilot this or provide support in some form.

fatnoah 6y ago
I find this interesting. As someone with over 20 YOE, I've always eschewed the "2-page" resume guidelines. My full resume ends up being 4-5 pages, even with rigorous attention to only a 1 sentence description of each role, avoiding duplication of facts, and keeping and bullet points in the form of "Did X, resulting in Y". I've always wondered if a longer format helps me more with automated resume scoring. Also, does LinkedIn come into play here? I feel like when I show up to an interview, there's a 50/50 chance they're holding my resume vs. a printout of my LinkedIn profile.
- cl42 6y ago
  Yesssss... That's part of the issue here. I feel like people optimize for keywords because the applicant tracking systems today optimize for keywords. By the time a hiring manager gets to a resume, you've likely been filtered several times... The challenge is those filters suck. Hence our approach to making it "conversational" or flee-flowing. Using word embedding and other clustering helps a lot. Knowing nothing else, I'd say keeping your resume to 2 pages is critical... And make your "about" section on LinkedIn really stand out with a few key accomplishments. If you'd like, shoot me your resume at hello@phaseai.com and we can give you specific feedback.
  - fatnoah 6y ago
    I appreciate the offer to help, but my general success rate is high enough that I don't want to mess with stuff. I do target my pursuit of opportunities, and I ALWAYS rewrite my resume so that it prioritizes the experiences and skills most relevant to each job. If I were to ask for anything, it'd be something to highlight those matches.
    - cl42 6y ago
      Amazing. If I had a penny for every job seeker who told me they don't do any resume customization... I'd have lots of pennies! :)
karagenit 6y ago
Cool stuff - reminds me of a semester project I did about a year ago using latent semantic analysis to find relationships between documents. Sounds similar to what you guys are doing, trying to pair job descriptions with the best fitting resume. I'd love to hear more about the technical details on your solution, though I suspect that's somewhat of a "trade secret" ;)
- cl42 6y ago
  A big part of what we've been doing focuses on word embedding models and classifying individual parts of the document. The word embeddings help us look for synonyms general ideas around what the recruiter is looking for, versus what we are finding. We also score individual sections to see if the sections themselves cover all the bases or if it's the resume as a whole. We've also explored building our own universe of words/terms to help with this, but that's a 2.0 sort of dream, at this point!
sqrt17 6y ago
err ... it's kind of what you'd get from Textkernel or LinkedIn Recruiter, probably at a similar price. But with nicer fonts, so ok.

by cl42 6y ago

Hi folks! OP here + author of the NLP algorithms in the post. If you're hiring and want us to help you with filtering like this, we're definitely keen to pilot this or provide support in some form.

fatnoah 6y ago

I find this interesting. As someone with over 20 YOE, I've always eschewed the "2-page" resume guidelines. My full resume ends up being 4-5 pages, even with rigorous attention to only a 1 sentence description of each role, avoiding duplication of facts, and keeping and bullet points in the form of "Did X, resulting in Y". I've always wondered if a longer format helps me more with automated resume scoring. Also, does LinkedIn come into play here? I feel like when I show up to an interview, there's a 50/50 chance they're holding my resume vs. a printout of my LinkedIn profile.

cl42 6y ago
Yesssss... That's part of the issue here. I feel like people optimize for keywords because the applicant tracking systems today optimize for keywords. By the time a hiring manager gets to a resume, you've likely been filtered several times... The challenge is those filters suck. Hence our approach to making it "conversational" or flee-flowing. Using word embedding and other clustering helps a lot. Knowing nothing else, I'd say keeping your resume to 2 pages is critical... And make your "about" section on LinkedIn really stand out with a few key accomplishments. If you'd like, shoot me your resume at hello@phaseai.com and we can give you specific feedback.
- fatnoah 6y ago
  I appreciate the offer to help, but my general success rate is high enough that I don't want to mess with stuff. I do target my pursuit of opportunities, and I ALWAYS rewrite my resume so that it prioritizes the experiences and skills most relevant to each job. If I were to ask for anything, it'd be something to highlight those matches.
  - cl42 6y ago
    Amazing. If I had a penny for every job seeker who told me they don't do any resume customization... I'd have lots of pennies! :)

karagenit 6y ago

Cool stuff - reminds me of a semester project I did about a year ago using latent semantic analysis to find relationships between documents. Sounds similar to what you guys are doing, trying to pair job descriptions with the best fitting resume. I'd love to hear more about the technical details on your solution, though I suspect that's somewhat of a "trade secret" ;)

cl42 6y ago
A big part of what we've been doing focuses on word embedding models and classifying individual parts of the document. The word embeddings help us look for synonyms general ideas around what the recruiter is looking for, versus what we are finding. We also score individual sections to see if the sections themselves cover all the bases or if it's the resume as a whole. We've also explored building our own universe of words/terms to help with this, but that's a 2.0 sort of dream, at this point!

sqrt17 6y ago

err ... it's kind of what you'd get from Textkernel or LinkedIn Recruiter, probably at a similar price. But with nicer fonts, so ok.