There’s a lot of talk these days about “fake news”, and for good reason. But the growing uneasiness about relying on information from the web has crept beyond politics into other areas, including the search for employment. Scams and fake offers are an unfortunate reality of online job searches across industries.
The data science world in particular has been swirling with skepticism, not just over whether job offers are legitimate, but about the job title itself—that is, over the tendency for some tech professionals to falsely label themselves as data scientists in the first place.
If you’d like to grab some tips for telling the scams, cons, and poppycock from real and worthwhile job opportunities in data science, read on.
Fortunately, it’s not too hard to plot a safe course through the labyrinth of hype surrounding data science work. Keep your eyes peeled for these red flags while scanning listings:
The science of big data has spawned plenty of pop culture chatter, with trendy buzzwords throwing up lots of smoke whether there’s much fire there or not.
A perfect storm of media hype, canned coverage, and recycled talking points makes discourse about data science watered down by the excessive repetition of significant terms of art like Artificial Intelligence (AI), machine learning, big data, the Internet of Things (IoT), master data, analytics, digital transformation, and others. As you browse listings, get in the habit of looking past the jargon for substance in job descriptions, details about required qualifications and experience, and concrete expectations of performance.
Beyond the style of writing they use, the overall level of professionalism and polish in correspondence you receive from job contacts can be a red flag. Something to remember is that all real data science companies have good writers on staff. Some fake jobs do too, of course, but bad writing is a clear sign of a scam. Red flags include punctuation, spelling, capitalization, and grammatical errors that no careful college student, let alone a high-tech business, would let slip.
In this day and age, no real company is difficult to find and learn about extensively through a simple web search. Having a clear web presence doesn’t guarantee that a data science company taking applications is worth your time, but it is a prerequisite.
There are ways to vet apparently legit organizations: double-check the spelling of company names with an additional search just to confirm that you’re not dealing with a clever impostor. And if you copy/paste text from official correspondence into a search engine, you’ll find out fast if it’s been copy/pasted and reused by scammers.
Some things really are too good to be true. And when transactional relationships appear to be, they usually are. Indicators include receiving the job offer immediately after a brief phone or online interview, as well as being cold-called by a tech company whose representative claims to have found your resume online, to want to interview or hire you right away, or the like.
An ounce of prevention goes a long way. Job boards are notorious breeding grounds for predatory scam artists prettying on credulous job-seekers. Instead use job sites with privacy policies and a commitment to vetting employers before allowing them to use the site to find new hires.
Requests for Your Money or Confidential Information
Real tech companies won’t ask you to fork over cash during the opening stages of discussion about employment. Remember that asking for money can take the form of requiring the purchase of software, digital services, or having your financial status verified through a credit report. In one standard scam, someone posing as a company rep will offer to send your resume to someone paid to edit it for resubmission.
Like any other flourishing field, data science has its share of weeds. But fortunately, for every fake job, scam, or overgrown, overblown hype surrounding work in the tech industry, there’s a simple strategy for sniffing it out and sidestepping it effectively on your way to a real and worthwhile job. Keep the tools we just reviewed in your pruning kit and gather ye rose-buds etc. etc.
Christian Golden, PhD, writes about tips and trends in digital marketing and social media for TrustRadius. He is a philosopher by day who loves teaching and digging into the big questions. His extracurricular interests include making music, reading comics, watching (really old) movies, and being in the great outdoors.