6 min readfrom Data Science

Hiring Manager: Fake Candidates and Cheating

Preface: This is a burner account for ... reasons.

About Me: DS hiring manager for a F500 company. My company hires a combination of on site, hybrid and remote roles.

Overview: Through the past 1.5 years, hiring has become untenable due to lying, cheating and now fake candidates. If you are unaware of what I mean by fake candidates, read this article. I'll briefly touch on the lying then focus the rest on the cheating / fake candidates.

Lying: For roles where we cannot provide sponsorship, we have a survey during the application process that asks if you require sponsorship or will require sponsorship in the future. Those who hit "Yes" are immediately filtered out. The problem comes from those who are either lying or confused when they hit "No".

90% of the people who submit "No" either lying or confused are on OPT visas. These are post-Master's degree visas that allow you to work for 12 months in your field with an addition 24 months added if you are a STEM field (so 3 years total). When assessing someone's profile for 30 seconds it is immediately obvious:

  1. Last work experience outside the US

In these situations the candidates either are lying or don't quite understand that when we say "or will require sponsorship in the future" it applies to people when cleared to work for 3 years. While these candidates pretty much exclusively originate from one country, please do not disparage my post with racial insults. These are people who simply want to work a job the same as you and I. It also does not make one more prone to lying. For every un-honest applicant we get, there are 2 others who apply honestly and are filtered out.

How does this impact you? Well we are getting 1,000s of applicants for these jobs. Because I do not discriminate on candidate name before opening a profile / resume, this means I spend a lot of my time (30s to 1 min) on candidates who are ultimately ineligible. Because I do not have all day to do this, it means I do not look at every candidate profile. Due to that, there is a chance that I will never see the profile of an eligible, qualified candidate.

That is all I will say on this. Again, do not post racial insults in the comment section.

Fake Candidates: Okay so let's now say I found a "candidate" who on paper appears eligible for our job. That is roughly 60% of the total applicants we get. Out of that 60%, 90%+ are absolutely fake candidates / people.

Below is a list of the key things that identify fake candidates:

  • Resume is an LLM generated recycle of our job description with no details, just buzz words and bold lettering
  • Phone area code also has no connection to education or work experience (appears a lot of bot farms are in Florida, Texas or Kansas)
  • They will say they work remote for companies that are notoriously in office or had a big RTO within the timeframe of their current work experience
  • Home addresses are non-residential or PO Boxes (someone applied with an address that I google street viewed was a highway overpass)

EDIT: Forgot email addresses like John.Doe.Dev@gmail

So if the resume isn't a dead give away, here are the next stages

  • Linkedin profile URL is legit, not a name and alpha numeric but there's slight discrepancies between resume and profile

Assuming I have not filtered you out from the above and the profile looks good, I will pass you to our recruiter to screen you. In these cases 50% of people I pass will still end up being fake! Our internal recruiter will catch things that are fishy, most often being its clear the person talking is not the one we saw on Linkedin. In these cases, the fake candidate is piggy backing off a real person's profile.

Cheating: Okay so now you are a real person at least and you're interviewing with us. Well unfortunately 50% of these candidates are using AI to cheat. We are very explicit at the start of an interview. We ask you not to use AI because we want to assess your education and experience. Its not that we don't use Windsurf or Codex ourselves but I need to know you'll understand what the LLM spits out and you aren't just a vibe code hero.

About a year ago cheating was more straightforward. A candidate would screen share only a tab, not their whole window. They would have a second monitor and by typing or copying some code into an LLM to generate a response.

Now the thing is voice to text or voice to voice technology. We will ask questions that are robust to copy-paste LLM cheating but the candidate has an app on their phone in their lap which will capture our question then show a response in text or send voice to their headphones. Dead give aways here are long pauses between our question and their response in a manner that is clear they are not actually thinking or looking down at their crotches a lot.

What can you do to stand out?

  • As much as I hate it, you need a Linkedin, you need it to have pictures of you (do not use any AI program to touch it up) and you need to genuinely engage in your industry and with old or new coworkers. This is the easiest way to confirm you are real
  • Create a unique URL for your linkedin page. Do not keep it as the base name/alpha numeric
  • Do not use any generic resume formatting for your resume. Create something that looks professional, is nice but unique to you.
  • Do not use LLMs to clean up your resume, focus details on very specific pieces of work you did that used a technology, don't just say you have CI/CD experience
  • If you fear discrimination based on your name, I would recommend putting that you are legally authorized to work in the US (though it sucks I have to say that)
  • Add something unique to your resume. If you made a medium post while working at an old job add it. Anything to stand out from fakes
  • Within the interview stage, always share your full screen and try not to wear headphones. That will help us not suspect you are cheating.
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