Insights vs Product vs Engineering Data Science, and how each provides value to your business

Data science roles in tech businesses fall into three categories:

• Insights. Using data science to understand users, products and businesses.
• Product. Using data science to test and optimize a product or feature.
• Engineering. Building models and data, which are then integrated into product features or used by other stakeholders in the organization.

These approaches can be very different in practice, requiring different tools, expertise, and operational processes. Nonetheless, businesses are only starting to differentiate these forms of data science. By properly differentiating these roles, businesses can more effectively hire, cultivate, and retain data science talent.

In this article, we will discuss the differences between Insights, Product, and Machine Learning data science. Below is a summary of the key differences and examples of each application. We will view these practices through the following dimensions: goals, deliverables, and tech stacks.

• Purpose. What is the fundamental role of the data scientist? What stakeholders do they partner with? How do they provide value to the organization?
• Deliverables. What types of outputs do…