Building Data Science Teams
Three Roles Your Data Analytics Team Must Have
We often hear about our clients developing in house capabilities for data analytics and predictive modeling. Immediately following these confessions are a common barrage of questions, such as, who manages your DST (Data Science Team)? What qualifications do you have for your data scientists? And of course the, How do you create those awesome interactive visualizations?
This post will answer some of the team leadership and structure type questions, but more importantly describe three of the most important roles.
To ensure your DST provides the greatest value, essential support roles are required in addition in the traditional data scientist. These roles include: data evangelist; contextual analyst; and data visualizer.
1) Data evangelist: This position does not require formal data science training, but rather an expertise in a specific business area, as well as a curious nature and a desire for finding new business uses for big data. We have found that individuals that have respect for the scientific process and tend to challenge the status quo tend to succeed the most in this role.
This role is both internal and client facing, spending time understanding client needs and identifying use cases for data. This individual leads our DST.
2) Contextual analyst: This role makes data products qualitative with a quantitative spin. It is not a programming role, but a background in programming will enable this individual to collaborate with the data scientists more effectively. The contextual analyst’s role is to understand the meaning of data, which not something an algorithm can do. We have found that this is a more seasoned individual that can develop evidence-based strategy.
In our organization, this individual is heavily involved at the exploratory and post-modeling phases to provide that extra layer of contextual understanding to drive really effective insights.
3) Data visualizer: This role evolves the output from the contextual analyst to a roadmap for an end-user deliverable. This is a position that requires brand builders, content developers, and other visually-oriented individuals capable of turning big data into innovative “instinctual graphics” that go beyond conventional bar charts and line graphs.
In our organization, this individual is engaged with the project from the beginning and quite a bit of prototyping is done to ensure the data story can be told from multiple perspectives without misrepresenting the data.
Many organizations struggle with marketing, strategy and business operations teams adopting data-generated insights and use them to make an organization more effective. The three roles above are essential to ensure use of the data products and that the DST is seen as a value by all stakeholders.
Depending on the size of your organization, one or two people can fulfill all these roles (background and experience permitting), but your DST needs these functions.
