Should graduates be worried about this data science gap, and what can they do to improve their chances of getting a job?Yes, the demand for data scientists is still high…There is some misinformation going around that data science has had its heyday..What’s more, LinkedIn’s 2017 Emerging Jobs Report on the fastest-growing jobs in the US (based on their user data) highlights that “[t]ech is king,” and the platform states that jobs with titles such as machine learning engineer, data scientist, and big data engineer are highly sought-after across a range of industries.This report, which analysed data from job posts on LinkedIn over a five-year period, notes that 6.5 times as many data scientist positions are posted today than in 2012..An application that may have looked attractive five years ago might today be put on the rejection pile.BUT… is this really the full picture?The Huffington post claims that there are approximately 1.5–3 million data scientists in the world right now — are there really no candidates with the right experience?What if I told you, the people responsible for this “Gap” aren’t really the data scientists; rather the directors, HR departments and even the recruiters in different companies.Why?The truth is, data science has become a buzzword, a hype..But the real problem is that they don’t know what a data scientist really is, what they do, how a team is configured, what makes a great data scientist really “great” — there is a huge gap in knowledge of the profession itself.There are plenty of data scientists out there, there are thousands of talented professionals that could easily flip a pre-data business up on its feet, but they are rarely given the chance to prove themselves..Most companies, in a rush to “hire a data expert”, assume that they need a 5–8 year experienced individual to solve all their problems (even though, ironically, the field hasn’t been alive for many years) and they conclude that every data scientist out there with less than that experience is no good.Fortunately, this means opportunityIt wouldn’t be fair to push blame and say that everything is due to ignorance on the profession — we data scientists are also to blame. It shouldn’t be surprising that HR has probably been doing its job in a traditional way, therefore it’s completely normal for them struggle with these new job positions..They are looking for degrees in our data science careers that don’t yet exist, they want experience where there was no field to get it from, they want skills that they don’t clearly understand… yet.It’s up to us to showcase our strengths, capabilities and what we can really bring to the table..Data is the future of business, there’s no going around it — and we know this, so let’s show everybody else what we are made of.But how do we do this?We should try to narrow the data science gap.6 ways to fill the data science gapSo how should we position ourselves to ensure that we get the job we want?.Sage advice: prospective jobs that cite a long list of methods and software you need to have knowledge of only shows how little a company understands of its data strategy, its data requirements and not to mention “they’ll hire anyone because they think that hiring any data person will fix all of their data problems.”6..Reconsider if you really want to be a data scientist..Speak to other data scientists on Twitter, reach out to them on LinkedIn, or join a discussion on Reddit.If you want to step up your game, there is a super friendly, informative and relaxed event coming up that can get you started in building your networking skills: DataScienceGO, a career-focused data science conference.More than ever, new data scientists must learn how they can create a reliable pathway to achieving their career goals..And hurry, our early bird tickets are selling out fast!Get your Ticket here!Don’t quit now!Ultimately, as good data scientists, we must look at the evidence rather than focus on conjecture.The truth is that data gives companies the information they need to get ahead of the competition, and they therefore address the single most important need of business: to make money.. More details