You may have heard the ongoing stampede in the enterprise world, as companies hurry to embrace “big data.” The term itself is loosely defined; we view it as innovation using the wealth of data to change how businesses operate. For companies, the upside is enormous. It means more intelligent decision-making as well as enhanced technology infrastructure, which at an enterprise scale easily translates to millions of dollars of value brought to the table.
At DataJobs.com, our internal data indicates that data scientists make an average of 122,000 with the top quartile reaching quite high, at $170,000. We also find that data science group directors can be salaried at over 200K. We won’t reveal the list of companies offering the highest levels – that’s private – but we will say that Silicon Valley is the center of this booming market.
Data scientists are technical and quantitative wizards who translate mountains of messy data into clear strategy insights and powerful predictive capabilities. Data science professionals are skilled across a breadth of disciplines, effectively the mathematician-programmer-MBA trifecta.
They are notoriously difficult to hire – ‘unicorns’ of tech recruiting. Rare to find. Some execs think they have magical abilities.
Demand to hire data scientists is booming, but supply is piteously scarce. Not a recruiter’s ideal situation. There is a mad scramble, an abundance of companies jumping through hoops to court the same set of rarefied individuals. This of course has culminated in data science salary expectations rising with the tide.
My advice for the fearless recruiter: you need to hire one of these elusive data scientists. Yes, you have your work cut out for you, but with strategy there’s hope:
1. Data scientist bait: interesting data and fun problems
Time to go fishing. What to put on the hook? First, you need to understand data scientist mentality. They seek out challenging problems, and thrive in discovery and intellectual curiosity. They gravitate towards innovative environments where they have intriguing problems to tackle. So bait them with interesting data they will be able to play with, fascinating problems they will be able to solve. Sell them on how your company gives them the environment where they can dive in and satiate their curiosity endlessly. Try this, and you’ll discover they will bite.
2. Play big or go home
Money may not be the leading factor, but it certainly still talks. This is not the situation to be cheap and noncompetitive. Yes, this talent is expensive, though a common measure for data scientists is that their work should be able to generate at least 3x the cost of their compensation. Depending on the scale of the enterprise, the value multiplier could easily be 10x or greater. Bottom line is to treat data science compensation as an investment that is likely to pay back many times over.
3. Being passive will get you nowhere
Data scientists have many options for places to work, and they may actually seek you out if their current role is too rigid and not satisfying their intellectual curiosities. So, cast a wide net. Be ubiquitous across niche job sites everywhere. When data scientists are open to switching to a better company, you better make sure your job opening is discoverable, or else they’ll never get a chance to consider your company as an option.
If “data scientist” is on your list of open reqs to hire, we wish you more than luck. Be very aggressive, and you may just find that unicorn.
Frank Lo is the founder of DataJobs.com, a resource center and jobs hub for all things big data. Frank is also the Head of Data Science at Wayfair.
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