From the course: A Day In The Life of a Data Scientist

Centralized organization

From the course: A Day In The Life of a Data Scientist

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Centralized organization

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- So data science like organizations and structures, I think are different anywhere you go. I have some history with consulting. So I've seen a lot of different businesses and how they actually structure a data science team. One of the common ways to do this is you have different types of data science in all of your organizations. So sales will have a data analyst and marketing will have their own data analyst. And there's some best practices that are used around the business that all of these analysts use or maybe they don't use and they work within their own specialties. The way that I've seen be most successful is actually having more of a centralized data science organization. And so this organization, it like contains a lot of different things outside of just data scientists. So you'll have typically like your data warehouse or data engineering teams. So they're the ones that actually pulling in data and curating it for analysts or data scientists to use. You'll also have data analysts. They're probably a little less on the statistics side, but they are working closely with the business and you know trying to understand okay, this KPI or key metric was down this past week, why was that? And so they'll go off and they'll look at dashboards or maybe build dashboards to really, you know help give them an answer. And then you have the data scientists within the whole data science organization or you know data and analytics organization. And they're more of the hybrid of being able to utilize the you know programming and analytics side alongside with that business analyst mindset and also adding in the predictive nature of the work they do.

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