👥

Building a data science team

Here, we'll talk about how to build and structure your data team to meet your organization's needs.

Members of your team

You might be surprised to learn that data science isn't a single field, it's actually 3 different jobs. Each position uses a slightly different sets of tools to achieve their goals.

Data Engineer

Tools:

Data Analyst

Tools:

Machine learning scientist

Tools:

Data Science team structure

Once you've hired some data professionals, there are 3 main ways you can structure your data team.

  1. Isolated
    1. It can contain one or multiple types of data employees without any teams like engineering or product.
    1. This is a great team structure for training new team members and changing which project each team member is working on.
  1. Embedded
    1. Alternatively, it can be helpful to use embedded model where each data employee is part of a squad which also contains engineers and product managers.
    1. This model let's each data employee gain experience on a specific business project making them a valuable expert.
  1. Hybrid
    1. The hybrid model looks similar to embedded model but with additional sync for all data employees across all squads.
    1. This additional layer of organization allows for uniform data processes and career development regardless of which project and employee is assigned to.