What They Still Don’t Teach You About Hiring Big Data Talent

Dec 07, 2016

A recent AT Kearney study rues that more than 60% of the companies with even the most advanced of analytics capabilities and technologies are too short on data science and Big Data talent to make the most of the humongous data they have. Even as the likes of Apache keep churning out newer Big Data frameworks and technologies with a vengeance; corporations around the world are scrambling up their acts to beef up their Big Data teams. But since it looks like not enough skilled talent with a professional credential are on the market for everybody to hire, its dogs eating dog right now.

As in any war, the war for talent is won even before its begun; and not on the battlefields, but in the minds of its generals. (Pardon the Sun Tzu reference). So, here are a few quick tactical briefs that could bring you hiring glory even as you suit up:

OUTTHINK - A no brainer, ironically! Outthinking competition includes everything – right from positioning your employer brand dead out of the clutter, down to putting together a compelling proposition for the applicants – making it unputdownable, that’s the trick. Outthink. Are you hiring for a Unicorn? What’s so knock-out about your pay and perks? What’s there in your bag for those millennials? How many sponsored family vacations have you thrown in your offer? Then there are those things about the job per se. How about research-oriented projects that add value and qualify the talent for raises? Have you implemented gamification in the team to separate the wheat from the chaff? All these and more are actually industry practices that your competitors are using even as you glance through this article. So here’s what you do about it: Outthink them in new and creative ways to increase your talent value proposition.

OUTTRAIN : Your organization is only as competent as the sum of the skills in your talent pool. Hiring is one thing, but upgrading has done the trick for a lot of the biggest employers in data science across the world – so go ahead and implement a cross mentoring program – let the R specialist show the Python coder how it’s done! Connect the Elasticsearch guy with the Mahout engineer over a friendly meeting. How about a MOOC collaboration for platform-specific certification from a renowned institution? Remember, word spreads faster than wildfire in the Big Data talent community and pretty soon, you’ll have a queue of specialized and certified applicants in your ATS! Amen to that.

OUTREACH : Everyone who is your prospective hire, if you’re reading this piece, has a digital footprint. Are you tracking it right? And how much are you tracking, really? How much do you leverage social APIs in your ATS and assessment models? If your social media hiring goal is just to scroll to the bottom of your prospective employee’s LinkedIn profiles, the end is near. Talent outreach is a finer discipline now than it was yesterday. From tracking posts across social media to posting prospective problem-cases in technical community boards, everything is fair game. The new trend is integrated monitoring of potential hires across social channels and leveraging such insights to assess fitment with clinical precision. The outer realms of space are the limit here.

OUTSOURCE : When in doubt, offload! Data Science Central foresees 35% of captive analytics practices in major corporations being entirely or partly outsourced to specialized offshore providers by 2021. In all likelihood that will be surpassed well ahead of time. So get ahead and outsource projects that require complex capabilities to those who can deliver them – in ironclad contracts, of course!

Applying data science to hire data scientists, as ironic as it may sound, is more effective than the average HR manager of yore gives it credit for. Case in point being a particular large tech employer discovering that Ivy League grads who had, at some point in their careers, faced the toil that went with minimum wage-level jobs or internships, were likely to perform 25% higher than those who hadn’t faced such situations. Insights like these, as much as they sound straight out of Moneyball, are empowering a lot of companies to identify hitherto hidden patterns and get ahead in the war for Big Data talent. Where do you stand?

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