Notice to startups: You are doing data science wrong

This past weekend, we penned a piece over at GigaOM about the importance of integrating your data science folks into your engineering and product process.

For startups, data science should not be seen as a separate scientific initiative but as an integrated part of the product. Speed and efficiency are key factors to burgeoning companies; hiring and building out a team of data scientists, or more aptly named “data product engineers,” is paramount. Once you accept that data science is about building data products, you will see that your data engineers, contrary to popular belief, do not need PhDs. Instead, they need to be able to integrate into the core of your product and engineering organization.

Today, Tomasz Tunguz penned a terrific reply over on LinkedIn.

Weald points to a different model of data scientist, an engineer, not a statistician, who can perform queries and based upon some insights, improve the product with a few code changes and a push to git. I like Weald’s post but disagree on one point. I don’t think there is one type of data scientist, but five.

Great discussion happening over on the comment thread, have a look and chime in!