Nick Kolegraff

Nick is the Director of Data Science at Rackspace. He suffers from TADHD (Technology Attention Deficit Hyperactivity Disorder)...which led him into data science. In previous dimensions, he started and incubated data science at Fortune 500 companies while working for one of the worlds largest global management consulting firms. He got his start designing hardware devices for voice controlled medical beds and then became more interested in intelligent non-living things. Later, he designed and implemented scalable backend systems for predictive modeling products as well as a few production recommender systems for large retailers. His TADHD started in college where he was making HPC clusters in his basement to do math and building voice controlled potato cannons. Nick holds a BS in Statistics and a BA in Computer Science from the University of Iowa. In his free time, Nick enjoys mountain biking, rock climbing, hiking, and working on some of his open source projects.

Do you need a data scientist?

Data science is hard but it isn’t dark magic.

The question “do you need a data scientist?” came up a lot when I was a management consultant for a global firm that successfully incubated data science within a few enterprise organizations. It’s hard. The discussion is hard and the culture clash for data scientists is hard. Many approach data science as some dark magic from Hogwarts. It’s not. Investigating a hypothesis takes time. Spontaneously generating data and building a model against that data doesn’t work. Understanding who you need and how they will fit into your organization is challenging. Where do we put them? Who do they interact with? What is the hand-off? Who do we structure around the project? How do you execute a project? Even better, how do we make MONEY? Yet, before we go there, perhaps we should step back a bit and think of this as a strategic question. Because maybe you do need a data scientist and maybe you don’t.

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