How To Build A Successful Data Science Team

Are you looking at how your team operates in the correct way?


As an industry, those working with data have realised that data science is more than just the sum of one person. Data science is essentially an art, it may need to use the same tools or follow similar protocols, but ultimately the results that are achieved can vary considerably.

In order to create the end result that people want, it is important to not only concentrate on the strengths of one person or leader to create what is required. This means that as well as getting the best possible people in, creating a well rounded and productive team is vital to long term success.

Below, we have outlined the 4 most important aspects to have within a data team:

Technical Knowledge

Starting with the most obvious aspect first, each team needs to have technical knowledge around data.

However, this is not simply the knowledge of how to use the systems, mine data and analyse it. It requires knowledge to identify anomalies, notice trends and most importantly, where to find them. It is undoubtedly the most important aspect of any data science team, it is the creation of the divisional product.

Ability To Communicate

I know of one data leader who has employed a journalist just to effectively communicate the findings from her team to the board and others within the business. It means that there is an implicit understanding by the journalist of how the technical members work and this can then be translated to non-data orientated stakeholders.

This is not purely through presentations and reports though.

Bringing a journalist in-house is an extreme measure, but there are other ways to communicate data. Data visualisation for instance has a leading role to play in communicating complicated data sets to others within the business. Having somebody in the team who can not only understand the data well enough to create visualizations, but also has the skills to do this in a way that translates for business leaders, is invaluable.

Business Acumen

Creating a data team that can process information and notice trends is not enough any more though. Simply relaying data to people is never going to work for those without an implicit understanding of what this data means in the business world.

Therefore, the team needs to have somebody with the ability to not only see the trends and communicate them. They need somebody who can put them in the context of the entire business. What does it mean for the business if there is a spike in a certain type of customer? Is this an opportunity?

Wider Company Understanding

Understanding the company as a whole is vital in the context of a data team. Knowing what to look for can only be the case when the wants and needs of the company are understood.

This comes from having somebody in touch with the wider company and who can communicate these requirements back to the data team. This is more than just pulling up a report or receiving an email, it require intuitiveness and the ability to predict what needs to be achieved by external divisions.

These four aspects alone, will not make the perfect data team. That is something on which a PHD could be written, but by looking at these aspects, it will be creating a firm foundation on which one could be built. 


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