Skip to main content
Domino's logo

Who is Domino?

Domino Data Lab empowers the largest AI-driven enterprises to build and operate AI at scale. Domino’s Enterprise AI Platform provides an integrated experience encompassing model development, MLOps, collaboration, and governance. With Domino, global enterprises can develop better medicines, grow more productive crops, develop more competitive products, and more. Founded in 2013, Domino is backed by Sequoia Capital, Coatue Management, NVIDIA, Snowflake, and other leading investors.

Watch Demo
  • Platform

      • AI infrastructure
      • Data management
      • AI workbench
      • MLOps
      • AI governance
      • FinOps
      • Pricing
      • Security & compliance
      • What's new
  • Solutions

    • Industries

      • Life sciences
      • Finance
      • Public sector
      • Retail
      • Manufacturing
    • Use Cases

      • Generative AI
      • Cost-effective data science
      • Self-service data science
      • Model risk management
      • Cloud data science
  • Learn

      • Events
      • Blog
      • Podcast
      • Courses and certifications
      • Data Science Dictionary
      • Documentation
      • Support
      • Demo hub
  • Company

      • About
      • Why Domino
      • Careers
      • Sustainability
      • News and press
      • Partners
      • Customers
      • Contact us

© 2026 Domino Data Lab, Inc. Made in San Francisco.

  • Do not sell my personal information
  • Privacy policy
  • Terms and conditions
  • Security
  • Legal

Episode 29

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

Data Science Leaders | 36:50 | December 01, 2021

Data Science Leaders: Kli Pappas

Listen how you want

Listen onSpotifyListen onAppleListen onYouTube

Return to podcast home

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

About the Show

Leo Reyes

Leo Reyes

Global Head of Data Science, Data & Technology Solutions

Episode 102October 29, 2026

Measure everything except the thing

Listen Now | 36min
Stephen Hahn, M.D.

Stephen Hahn, M.D.

Chief Executive Officer (and 24th Commissioner of the U.S. FDA)

Episode 101

See why Fortune 100 data science leaders choose Domino

Watch DemoWatch customer stories
Home
Watch Demo
Watch Demo
October 07, 2026

The data behind the fastest vaccine ever

Listen Now | 30m
Justin Johnson

Justin Johnson

Former Executive Director, Data Science Platforms, Oncology R&D at AstraZeneca

Episode 100August 24, 2026

Becoming the builder-conductor

Listen Now | 30:04