Hiring the right person for any job is difficult, we all know that. But it’s exceptionally difficult when you have little or no idea what you’re looking for.
This is a key problem for many when making hires in big data and data science. I am speaking from my experience as a big data and data science recruitment consultant after having spoken with many hiring managers - from CEOs to analytics managers to team leaders (and everywhere in between). What I have discovered are the key problems we face in the UK when making hires in this fresh and innovative space.
As Bob Dylan said, “a mistake is to commit a misunderstanding”. Where there’s a lack of understanding, there will always be problems. The data professionals of this world will have no trouble in grasping big data concepts, as many of these have been around for decades, though they may not have been applied to this much data. Where the trouble begins is when the technical professionals are not actively involved in the recruitment process from the start. This is why you will see many adverts with wrong salary ranges, littered with buzzwords and applying job titles incorrectly, eg, “data scientist” to glamorise “business analyst” positions.
Beware of the Catch 22 that seems to be trending. Picture this: the job description says you need at least two years’ commercial experience of Hadoop, but to get commercial experience of Hadoop, you need at least two years’ commercial experience of Hadoop? What?
Before driving headlong into a big data and data science hiring push, find out how this could really add value to your organisation. 360i's Kevin Geraghty eloquently states that, “data science is not voodoo. We are not building fancy maths models for their own sake. We are trying to listen to what the customer is telling us through their behaviour.”
Perhaps your data team already has some excellent analysts and developers? Then perhaps invest in sending them on training courses, rather than making a new hire. Analysts already in your company are familiar with your data, consumer base and company ethos, so will be able to hit the ground running when applying big data. And not to forget, investing in training helps to retain staff.
Universities such as UCL, Imperial, Sheffield and Royal Holloway (to name a few), along with the Open Source communities, are moving quickly to make sure there are options on offer for data experts to transition into the world of big data and data science. When looking at someone who has transferable skills, say a physics post-doctoral researcher, distinguish the ones who have done extra-curricular work. Are they passionate about programming? Do they have a GitHub account? Have they participated in Kaggle? Have they completed free online courses? Very often, you don’t necessarily need to hire the right skills but the right attitudes, as the latter cannot be trained.
When looking to make hires in this new space, you need to consult with someone, for free, on what the market looks like. As a big data and data science specialist recruitment consultant, I spend all day, every day mapping the market, finding opportunities and helping companies of all sizes to make hires. As we enter an age swarming with data, those that can embrace and master their data will create better products, services and dominate their industries. Remember, as LinkedIn’s Jeff Weiner puts it, "data really powers everything that we do”.