Alan Jacobson, Alteryx’s Head of Data and Analysis, talks about leading data scientists who create tools for use by other data researchers.

Picture: Diogo Nunes on Loosen

Some of the best data scientists I’ve ever worked with have had an incredibly different background.

Builbuilding a successful team – and this isn’t just about data science; it’s true, I would say, for most, if not all, teams – one of the good arts is building a very diverse group of people. And a science that is very clear: Diversity produces better results for teams.

Which machine are you interested in boarding?

Let’s say you get on a plane, and I can show you all the math of the model we’ve designed the plane with. I can show you completely openly all the formulas and all the math. Glorious. Or I can tell you that we flew a million times and we have a model that worked 100% of the time. Want to be on a 1,000 001st flight?

Take professional language and use examples that we can all illustrate in our daily lives.

Data science is certainly not very hard. There are, of course, concepts in knowledge that are more difficult than others. But most practicing data scientists do – it’s not thermodynamics. Thermodynamics was a very difficult course. At least for me, it was a really difficult course. Multidimensional calculation. It’s a pretty abstract, hard-to-describe thing.


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