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Neural Foundry's avatar

Superbly articulated mapping of PDS in the datascience landscape. The distinction beween analytics (what happned), ML (what will happen), and PDS (what should we do) is powerful because it highlights a capability gap most companies don't recognize. The framing of PDS as a learning partner rather than a metrics team completely shifts the conversation around experimentation from validation tool to strategic decision function.

Maxime Chung's avatar

I have often found it difficult to get clear explanations from data professionals or professors about the differences between analytic data science, product data science, and marketing data science...etc., especially since the term ‘data science’ is used so broadly by recruiters and can be hard to get to speak and verify with hiring managers. I appreciate this article, and I will use it as one of the tools to help shape my career trajectory as a data science student

Banani Mohapatra's avatar

Amazing!! Thanks for the read and the purpose was to give an overview of what is out there and how product data science is developing as a niche that companies are pivoting to.