Building an Analytics Team

Abstract: Based on her experience of building analytics teams from the ground up, Hillary will walk through the process of creating an analytics team.
We’ll begin by examining why analytics teams exist and how they are different from Data Science teams. Next, we’ll discuss possible structures for analytics team, including embedded, independent, and hybrid structures.
We’ll talk about best practices in hiring a diverse and talented analytics team, including good interview questions, and interview tools, such as CoderPad to ensure that applicants have the necessary skill set.
Once the team is up and running, it needs to integrate with Product teams. Creating best practices around data creation and experimental design, can make sure that your team is involved early, before problems can surface.
Success can bring challenges, such as too many under-defined requests. Creating a ticketing system unique to your team can ensure that ad hoc requests can be handled in a systematic and efficient manner. This is key to scaling an analytics team.
There are many approaches to becoming the voice of data at a company. Building a data reporting ecosystem ensure that all internal clients have access to what they need when they need it. The talk will cover dashboarding, alert systems, and data newsletters. Finally, we’ll discuss promoting responsible data conception through continuous training in statistics and tooling for all members of an organization.

Bio: Hillary is a Senior Curriculum Lead at DataCamp. She is an expert in creating a data-driven product and curriculum development culture, having built the Product Intelligence team at Knewton and the Data Science team at Codecademy. She enjoys explaining data science in a way that is understandable to people with both PhDs in Math and BAs in English.