Featuring industry luminaries Nate Silver, Cathy O’Neil, Wes McKinney plus speakers from Airbnb, BlackRock, Deloitte, Galvanize, UnitedHealth Group, and more

SAN FRANCISCO, Calif.— April 4, 2018Domino Data Lab, provider of the most advanced data science platform, today announced featured speakers who will present at the inaugural Rev summit for data science leaders and practitioners. Keynote presentations will be delivered by Nate Silver — founder and editor in chief of FiveThirtyEight and the author of “The Signal and the Noise: Why So Many Predictions Fail — But Some Don’t” and Cathy O’Neil — author of mathbabe.org and the book “Weapons of Math Destruction.” Other speakers include: Elena Grewal, head of data science at Airbnb; Jim Guszcza, chief data scientist at Deloitte Consulting; and Wes McKinney, creator of pandas project and senior vice president and software architect at Two Sigma.

The conference will take place May 30-31, 2018 at the Yerba Buena Center for the Arts in San Francisco. Rev will offer two days of interactive sessions on how to run, manage, and accelerate data science as an organizational capability.

“In our conversations with hundreds of organizations across a wide swath of industries, sizes and locations, we’ve found that current and aspiring data science leaders need a space to learn, collaborate, and discuss how to elevate data science’s role in organizations,” said Nick Elprin, co-founder and CEO at Domino. “We created Rev to fill this need, expanding on the success of the Data Science Pop-up series which has seen growing momentum among thousands of attendees over the past two years.”

Attendees primarily represent data science management and practitioners, along with IT architects, business analysts and executives. The conference will be comprised of two tracks:

  • The Practitioners track focuses on technical use cases, best practices and methodologies to help data scientists do more of the work they love with speed and efficiency. Sample sessions include “Unit Testing for Data Science,” “Using Git for Data Science,” and “Data (Science) Ethics.”
  • The Leadership track guides data science managers on their journey to make data science a core business function while sharing best practices for recruiting, retaining and scaling the team. Sample sessions include “Aligning Data Science with IT,” an “Internal Practices Facilitating Data Science Collaboration and Faster Innovation” panel discussion, and a limited-availability “Best Practices for Managing the Data Science Lifecycle” workshop.

For Domino customers, Domino will also host post-conference training at no additional cost to Rev attendees. The training will take place Friday, June 1, offering two three-hour courses: “Workshop: Build and Deploy a Chatbot in Domino” and “Domino Compute Environments Training and Certification.

To learn more about Rev or to register, visit rev.dominodatalab.com. Early bird ticket prices ($395) expire April 15.

Additional Resources:

  • A survey report summarizing feedback from more than 250 data science leaders and practitioners reveals factors that enable data science teams to achieve return on investment (ROI), top capabilities contributing to their success, and priorities. Download the full report here.
  • Gartner, Inc. positioned Domino Data Lab as a “Visionary” in its 2018 Magic Quadrant for Data Science and Machine Learning Platforms report. Read the report here.

Media Contact:

Karina Babcock, Director of Corporate Marketing

E: press@dominodatalab.com

About Domino Data Lab

Domino Data Lab provides the world’s most advanced data science platform, powering organizations that are using predictive models to drive their business. Companies including Allstate, Coatue, Mashable, Monsanto and startups alike use Domino to accelerate breakthrough research, increase collaboration and productivity of data scientists, and more rapidly deliver models to drive business impact. Founded in 2013 and based in San Francisco, Domino is backed by Sequoia Capital, Bloomberg Beta, and Zetta Venture Partners. To learn more, visit dominodatalab.com.

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