Big data is an overused term, and it makes some people — including me — shiver when CXOs use it randomly with other buzzwords. Thus, it comes as no surprise that Gartner, applying its hype logic model, declared in 2012 that big data might reach its tipping point soon (find here Gartner’s 2012 hype cycle). Thus, is the hype in decline? No – Companies have seemed to gear up.
A few weeks ago, I got a phone call. It was a headhunter from one of the top three worldwide executive search firms. The firm was looking for a senior manager who knows big data. The conversation that followed was riddled with the usual buzzwords: “evangelist” – “big data” – “hadoop” . . . “Our client is an international company in the insurance sector. They need someone urgently who can find the value in data,” said the headhunter.
That sounded like a surprise to me. An insurance company needs urgent help? Are they not the ones best positioned? Don’t they have many quants in-house who calculate our insurance? The insurance sector has the biggest “data value potential,” at least according to McKinsey (see MCK’s Study on Big Data from May 2011). And the salary? Be ready for the next surprise. US$1,061,000 (= 800.000 Euro). Hold on a sec. What?
Salary of USD 1,061,000 in cash for a data scientist!!!
This kind of offer shows you one thing: this company seems to be desperate to become data-oriented, and no, the hype cycle is not over (click to tweet). At least not yet.
Should you ride the hype for US$1,000,000? Maybe even change the model of compensation? You get paid per TerraByte you touch? Well, most likely, you shouldn’t take this job if you don’t love data. This offer shows something more than desperation. This company doesn’t know anything about data; it seems that they hadn’t even investigated what the price range for big data guys is (see here KDnuggets salary overview). You might want to double or triple those averages when you are looking for a senior manager.
All that this company seems to know is that their data has value, but they aren’t using it. Thus, this position is more than just a data job – it is a change management job. You do not need to understand analytics or speak Python or R. You need to know how to turn around a corporate tanker. What this company really needs is a senior-level VP. Yes, for this kind of job description, the salary starts to make sense.