Skip to content
    Data Science Leaders | Episode 29 | 36:50 | November 30, 2021

    To Patent or Not to Patent? How to Weigh the Options for Your Team

    Get new episodes in your inbox
    powered by Sounder

    Summary

    Transcript

    Should your team patent its data science work? With open source such an important part of the data science community, patents almost seem antithetical to the ethos of the field itself.

    But it turns out, there are some very good reasons to pursue data science patents in business.

    In this episode, Kli Pappas, Associate Director of Global Analytics at Colgate-Palmolive, shares his team's process for deciding whether to patent an algorithmic process—and what benefits it can bring. Plus, he talks about why a statistical background is so important for teams that generate data.

    We discuss:

    • The transition from getting a PhD in chemistry to the analytics world
    • Finding the balance between statistical and computer science backgrounds
    • Why you should patent your data science work and how to do it

    Popular episodes

    Embedding Responsible AI in Your Models and Your Team

    44:26 | Episode 34 | January 18, 2022

    Supply Chain Solutions and the Role of the ML Engineer

    38:04 | Episode 33 | January 11, 2022

    Legal Analytics: Winning Business, Winning Cases, and Winning...

    30:06 | Episode 32 | January 4, 2022

    See why Fortune 100 data science leaders choose Domino