Building Effective Data Science Teams


“Data and Goliath” –gouache painting by Jacqueline Nolis (image from her Etsy store)</sup?

So what does it take to build a successful data science team? Whether you are the first “data person” at your organization or leading a team of hundreds, we know success is not based on just technology; it requires people to create a productive, effective, and collaborative data science team.

Last month’s webinar featured data science leaders from Caliber Home Loans, The Looma Project, Saturn Cloud, T-Mobile, and Warner Music Group to start to answer this question.

Our panelists for this webinar were:

  • Kobi Abayomi , Senior VP of Data Science at Warner Music Group
  • Gregory Berg , VP of Data Science at Caliber Home Loans
  • Elaine McVey , VP of Data Science at The Looma Project
  • Jacqueline Nolis , Head of Data Science at Saturn Cloud
  • Nasir Uddin , Director of Strategy & Inspirational Analytics at T-Mobile
  • Moderated by Julia Silge , Software Engineer at RStudio, PBC

You can view the recording of the webinar at Building Effective Data Science Teams.

There were so many great follow-up questions that we’d like to keep this conversation going. We will dive deeper into specific topics through:

  • Future blog posts (Subscribe here)
  • Open meetup discussions with data science leaders - join this meetup group for an event on June 24th with John Thompson, Global Head of Advanced Analytics & AI at CSL Behring
  • RStudio Community

We’ve also added links to an RStudio Community thread for each individual question if you’d like to continue the conversation there as well.

We will summarize the questions and answers brought up during the panel that focus on three main themes that we think contribute to effective data science teams:

We have paraphrased and distilled portions of the responses for brevity and narrative quality.

Read on at:

This is a companion discussion topic for the original entry at https://blog.rstudio.com/2021/06/03/building-effective-data-science-teams