A lot of the heavy lifting involved in setting up data science at a startup is convincing the product team to instrument and care about data. If you’re able to achieve this goal, the next step is being able to answer all sorts of questions about product health within your organization.
A novice data scientist might think that this type of work is outside the role of a data scientist, but identifying key metrics for product health is one of the core facets of the role. I’ve titled this post as business intelligence, because once you’ve set up a data pipeline, a data scientist in a startup is expected to answer every question about data.
Author: Ben Weber