A Data Professionals Community

Practically Managing A Data Science Team

Operating a data science team is not something that can just be learned by watching lectures and videos on Coursera and Udemy.


Don’t get us wrong, they are great places to learn data science and machine learning theory with practice problems.

However, they don’t teach good business practices, and how to operate a data team in a business settings. Knowing algorithms, and how to use Hadoop is not enough to have an effective data team.

Advice To Data Science Teams

Teams have to work with other departments, they have to maintain software, report to executives, and of course, return business value! Data science, like analytics and business intelligence are just tools to help make the business more effective at making money.

None of this is discussed in most data science classes. That is why, one of our key focuses is not just custom data science algorithms and models, but also data science team development.

We wanted to offer some great tips that will help your data science team be more succesful. This has nothing to do with algorithms and models, and everything with how data specialist need to operate in a business:

ROI Vs. Algorithms And Technology

As programmers, data scientists, and engineers. Most of us often prefer to focus on the technical aspects of our data projects or software we are developing. The reasons we develop products is not solely money, but to prove that we can do something. It is a challenge! We are problem solvers.

Maybe we want to prove that we can develop an algorithm that can predict whether a product is a Hot Dog or Not a Hot Dog. Just for fun!

However, at the end of the day, us data scientists, data consultants, and software engineers are hired by businesses. At the end of the day, those businesses want to see fiscal results. It doesn’t really matter whether your use a neural network or a support vector machine based algorithm, which result either saves the most money, or brings in the most revenue.

It is important to remember, because the soon a data scientists or big data analyst can figure this out. The more effective they are in their role. Part of being a data scientists is having a slight entrepreneurial spirit.

Data specialists seek out opportunities to save the company money, or find new value streams. We are often right too, because we not only understand the business but we have the data to back our insights.

That is one of the values of having a data team that is well attuned with your business. They have data to drive their decisions…

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