Contrary to prevailing sentiments, I counsel patience with regards to hiring a data scientist. Firstly, I mean no disrespect to my data science colleagues, and many will likely agree with me because no one likes to enter an environment where sub-optimal results or failure are probable. Yes, it’s likely you need to add one or even a few data scientists to your team, but not as your first step into the wide, wide world of big data. Give me a few minutes and hopefully you’ll see it my way.
Sure, big data is, well big. And it’s scary. Especially to those of you who have not been around large data sets most of your lives. So you need help understanding it.
To put the problem in perspective let’s look at a medical analogy. If you have some discomfort in your chest, you don’t run to a cardiac surgeon and ask for bypass surgery. First you try to understand the nature of the problem and then go through protocols designed to make the discomfort go away. Even in the case of extreme circumstances, one goes through a diagnostic process, perhaps in an emergency room, to determine the best way to get “better.” I would submit that if your business situation is extreme with respect to big data, there are probably bigger issues with which to deal and you might need a different kind of specialist. A lot is going to depend on the size of your company or organization.
If you are a midsized to large global enterprise with lots of consumer-type customers, the need for big data usage may be more acute than in smaller companies, and at some point you may find that you need data science expertise in house. Smaller companies need to think very hard about on staff data scientists as the costs may outweigh the benefits. In either case hiring decisions should follow strategy, planning, budgeting, etc. Knowing what you need to do ahead of time will help to frame implementation decisions down the road, including and especially hiring.
What if you don’t have the knowledge to craft a strategy?
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