3 Remote Interview Scams Every Data Science Manager Should Be Aware of
Whether it’s the 30 second commute, unlimited snacks, or pants-optional lifestyle, remote work makes the daily grind more enjoyable in many ways. But it also introduces new challenges, especially in the area of recruiting.
As a data staffing and recruiting agency that sources and places data experts across the country, we’ve been using a fully remote screening process for quite some time. But over the past year, we’ve run into some surprising challenges in remote hiring that we did not see coming.
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The three most common types of interview fraud
In our ongoing blog series on the topic of data science resume fraud, we’ve shared lots of insights on recognizing falsified information in candidate applications. In this post, we’ll discuss how issues inherent in remote interviewing, such as internet connectivity issues, allow this type of fraud to be perpetuated all the way through the interview process, with some pretty brazen scams. We’ll also share our tips on how to recognize when it’s happening and what to do about it.
At Dataspace, we switched to doing all interviews via video after having one too many instances of obvious fraud during phone interviews. In one situation our recruiter asked a candidate about a particular data science tool listed on their resume, “Tell me how you’ve used X for a project?” After an awkward silence accompanied by audible keyboard clicking, we get a Wikipedia-perfect definition of the particular technology as a response with zero experiential information.
As surprising as it is that candidates will try to pull off such an obvious scam on the phone, it’s even more jaw dropping what transpires even when you can actually see the person. For instance, candidates still try the Google-it stunt even when they’re on video! (Dude, we can see you!)
Anyway, here’s a run down of are three of the most pervasive types of interview fraud we’ve experienced over the past year:
1. The Location Lies
(Or, if you say Huh-ston and I say Hue-ston, we’re gonna call the whole thing off.)
One of the more common scams we see, and probably the easiest to get away with, is the interviewee claiming to be located someplace they are not or having worked at a business they have never set foot in.
Sometimes the effort to mislead can be obvious. Recently we interviewed a data scientist on video whose resume noted that he had been living in Houston Texas for more than a year. But, throughout the interview he repeatedly pronounced it as “Huh-ston.” (For how many seconds do you have to be in Houston before you realize that it’s pronounced Hue-ston, not Huh-ston?)
We could also see that he was wearing a fleece, so we asked what the weather was like, to which he replied cold and windy. 30 seconds on Google was all it took to verify that the weather in Houston at that time was 86 degrees and sunny.
More subtle are employment misrepresentations. When you can work from practically anywhere, it’s trickier to spot falsehoods early in the screening process. We interviewed a candidate who claimed to have been working remotely for two years as a data engineer for a global insurance company. He talked at length about the project, and while his technical knowledge seemed on track, we sensed something was off. So we asked what department he worked in. He said, “products and shipping,” which seems pretty unlikely for an insurance company. He eventually confessed to his lie and tried to convince us that it didn’t matter, but it was too late to save his prospects for the position.
Yet another candidate claimed to work onsite as an analyst for a large company that’s located smack in the middle of downtown New York. When he couldn’t answer the simple question, “What’s it near?” it became clear that he did not have the experience he claimed. (C’mon, it’s New York! Just throw out two numbers and you’ve probably got a valid location—“Yeah, it’s near 53rd and third,” or “12th and fifth”—heck, they’re both addresses in NY, right?)
2. The Stand-in Scams
(Or, why it’s easier to get a job as a data scientist than to vote in some states.)
Another relatively common scam is to have someone different from the person on the resume show up for the interview. It could be because the stand-in has more in-depth technical knowledge of data science or engineering or because he presents better on video or even because the entire resume was fraudulent in the first place.
This type of scam can be hard to detect in real time because there’s no way to verify if the data scientist or engineer answering the questions on video is actually who they say they are. Legally (and for good reason), we cannot ask for photo ID or other proof of identification. But in the long run, this scam will only lead to placement if the recruiters are willing to overlook the signs of fraud. A thorough data science candidate screening process with multiple video interviews (like ours) will eventually weed out stand-ins. Not to mention, it’s impossible to hide the scam when our client has also taken part in a video interview, but a totally different analyst shows up for the first day of the job. (And yes that actually happened.)
3. The Response Ruse
(Or, “Cyrano, is that really you?”)
The most common scam of all is also the most painfully obvious. This is when answers are being underhandedly obtained by candidates during a video interview. There really aren’t a lot of terribly elegant ways to do this, but that doesn’t stop interviewees from trying.
As we mentioned above, the same old trick we’ve experienced during phone interviews is also attempted rather frequently during video ones: candidates try to subtly Google answers to our questions on a laptop placed out of view from the camera. It’s always surprising anyone thinks they can pull this one off.
More sophisticated is the use of an earphone to feed answers to the candidate, but the skill needed to pull this off is greatly underestimated. An interviewee will join the call with both a video and a phone connection. All the while, the phone line is being monitored by an expert who’s providing answers to the person on screen via the earphone. Pauses that go too long, facial expressions that don’t seem to match what’s happening, and lots of stall techniques are pretty good tells.
The absolutely most painful scam to experience as a recruiter—and yet this actually happens—is when the interviewee attempts to mouth the answers while another person is doing the speaking. We’ve even seen voice modulators used to try and mimic a female applicant’s voice. As you may suspect, this one is excruciatingly obvious when it happens. Again, dialing in with two lines is a dead giveaway that something is going to be off about the interview.
Amusing anecdotes aside, we truly feel bad for candidates whose situations are tough enough that such fraud seems justified, or those whose employers put them up to scams like this (we’ve heard that’s a somewhat common thing). However, for the sake of our clients and our own reputation, we do not countenance misrepresentations. As a result, we reject a decent number of seemingly good candidates because we just can’t feel sure of what we’ll see on the day the project starts.
Why is there so much fraud in data science hiring nowadays?
As a recruitment and staffing agency that works only in the fields of data science, data engineering, and analytics, we’ve noticed that the amount of fraud in resumes and interviews shot up significantly over the past year. While one element may certainly be that we have become better at recognizing it, there seems to have been a “perfect storm” of circumstances that have allowed it to grow so significantly:
- An increased demand for data talent – Data science-related careers are the fastest growing jobs in technology, and there’s no slow down in sight. It’s easy to see why—it’s estimated that each person creates 1.7 MB of data per second, which amounts to about 2.5 quintillion bytes per day, globally.
- A shortage of qualified candidates – For whatever reason, the U.S. does not seem to be creating workers interested in the highest-demand data science and engineering careers. Whether it’s a lack of technology education in public schooling, or a perception of job status for many data-focused positions, Americans are not raising their hands to fill these roles.
- The switch to rely solely on remote interviews – Remote work is nothing new, but the global pandemic pushed it to the spotlight. By the end of 2020, 71% of workers whose job was able to be done remotely had switched to telecommuting. With zero options for in-person screening, and the knowledge that you’ll never have to meet your employer face-to-face, the interview process is rife with opportunities to try to pull off a scam.
- Changes in immigration policy – When you combine the U.S. workforce’s lack of interest with several years of immigration clamp down, you even worsen the gap in supply, while demand is only increasing. Overseas engineers with limited opportunities may feel they have no choice but to turn to dishonest methods to find work in the US, even if they’re not actually in the US.
- Recruiters who know HR but not data science – On top of it all, the field of data science is highly specialized; each area and industry has its own set of skills, tools, and technologies. To be able to root out fraudulent applicants early in the process, hiring managers must be working from much more than just a checklist of the technical requirements for each position.
There are many staffing companies that specialize in helping data science talent from overseas secure visas and find high-quality work in the U.S. They are overwhelmed by the enormous demand in the states for data workers and the onslaught of foreign data scientists, engineers, and analysts interested in those jobs. Unfortunately, too many of these firms will not only encourage, but actually facilitate, the fraud that is happening in resumes and interviews.
A junior-level data engineer came clean with us about the reality of trying to get work in the U.S. through one of those less-than-trustworthy staffing companies. The agency provided a resume for him that was fraudulent and submitted his application to senior-level positions he wasn’t qualified for. Not only did they promise to help him get through the interview process by having a surrogate interview for him, they also told him if he got the job, he should call them whenever he didn’t know how to do what the client was requesting and they’d hook him up with an expert.
Tips to spot and combat fraud during an interview
Sadly, we now treat each applicant with suspicion until we’re comfortable that they’re for real. If something doesn’t seem right, we assume it’s not right. And it’s not just us, we know of big employers who’ve been stung and are taking the same approach. This is all a real shame because many of the imposters we speak with are quite good, they’re just probably not the people our client will end up working with.
While there may not be much we can do to change the current culture of hiring scams, there are some red flags that can tip you off as to when it’s happening during an interview:
- Unwillingness to use video – We quickly end calls if the candidate refuses to use a video connection. Pretty much everyone has access to a video connection these days so, if you’re not willing to use yours, what message are you sending?
- Poor internet connection – Not only can a laggy feed mean the candidate is farther away than they say they are, it can also give cover for all sorts of fraud, especially anything having to do with being supplied answers. From our experience, most video calls are pretty clean. If yours isn’t, I’m afraid that we’ll assume the worst.
- Dialing in to an interview with two lines – When an applicant joins their video interview with both a video and an audio-only connection, that’s almost always a sign something is up. Why do they need to do that?
- Unusually long pauses in conversation – While awkward pauses are part and parcel of video meetings in general, be on the lookout for patterns, especially when they are coupled with other red flags. You’ve got to agree that it’s probably a red flag when a candidate takes 4 – 5 seconds to ‘remember’ where their last assignment was. Right? (I mean, Dude, you worked there for two years? Where did you go each morning? What did the sign on the front of the building say?)
- Too many generic answers – Many candidates have been schooled in how to give broad answers that seem reasonable to non-data science experts. Again, look for patterns and an inability to back up those answers with examples. Better yet, have a data person on the call with you.
- Stall tactics, especially around connectivity – It should raise concerns if the candidate is repeatedly asking, “Can you hear me?” or acting as if your connection is frozen immediately after you ask a question. This is a popular way to try to cover the fact answers are coming from somewhere else.
As disheartening as it is to deal with, there are measures you can take to reduce the opportunities for fraud during an interview.
- Always perform interviews via video. You might do a quick preliminary interview on the phone but, with fraud so rampant, make sure you do your significant interviews via video.
- Ask specific, non-yes/no, non-leading questions to confirm details. When you need to confirm the applicant’s location. Questions about things such as the local weather or nearby landmarks can quickly indicate whether the candidate knows what you’d expect from someone with experience in that geography.
- If the candidate calls in with two lines, insist that one disconnect. There just aren’t enough valid reasons to need two lines for an interview. If they claim their computer audio is broken, then reschedule.
- If the connection is lousy, reschedule. Poor connectivity gives cover for all sorts of fraud, but especially being fed or looking up answers.
The new normal for data talent hiring
(…and you thought the phrase “new normal” died on 12/31/2020!)
Whether we like it or not, hiring scams are rampant, especially in the fields of data science, analytics, and engineering. And, thanks to the pandemic, many businesses and employees have now discovered the benefits of remote work, so remote hiring won’t be on the downward trend anytime soon. This is a reality HR teams, data science managers, and industry recruiters need to be prepared for.
While there are lots of good, and even great, data science and data engineering candidates who get caught in a situation where they are encouraged to perpetuate fraud, we can’t take the risk of extending a placement if there’s any doubt at all. We encourage all hiring managers to be diligent and look for the red flags we’ve discussed above. And when in doubt, get a data science expert on the interview with you—someone who knows the tools and technology—to help you identify and clarify shaky responses in real time, so you don’t waste any more time than you need to on a fraudulent candidate.
Do you need help to root out fraud in data talent acquisition?
We are data recruiters who are also career data experts (not professional headhunters). We know the industry inside and out and can help you spot employment scams and eliminate fraudulent candidates from your pool.
Contact us to learn more about our data talent hiring process.
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