Data Science

Coatue Management Leads $27 Million Investment Round in Domino

Nick Elprin2017-04-24 | 4 min read

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We’re pleased to announce that Coatue Management has led a $27 million funding round for Domino, which included our previous investors Sequoia Capital, Zetta Venture Partners, and Bloomberg Beta.

We have always been mindful not to celebrate fundraising too much. Raising a round — while lots of hard work and exciting in many ways — is not an end in itself. Rather, a new round enables us to reach our ultimate goal: building the leading data science platform to help companies maximize the impact of their quantitative research.

I have two main observations about why this is a critical milestone for us. The first one on this round, and the second on the kind of business we are building.

This round feels different because Coatue is not only one of the top investment firms in the world, but it is also a customer of ours.

Coatue has a large quantitative research team that uses data and advanced analytics to identify new investment strategies. The team has been using Domino’s platform to collaborate on and reproduce research for two years now.

Simultaneously, Coatue’s venture capital team determined that one of the most important trends to invest in over the next few years is the advancement of data science. They believe (as do we) that data science is reshaping almost every industry.

Coatue preemptively led our latest funding round. Prompted by our position in the industry, and by how much its analysts love the product, Coatue’s team identified the opportunity and invested. As a founder, I can tell you that it is deeply gratifying when one of your clients loves your product so much that they want to invest in your company.

This investment will enable Domino to pursue bigger opportunities, and we’re more excited than ever to accelerate the work we’ve already begun building on.

Since the funding that Sequoia led last year, we have seen our users triple, and our customers and revenue double. But that’s not the most interesting thing.

What’s more interesting is how diverse all these users are in terms of industries. They range from insurance to pharma to advanced manufacturing to internet technology. Most industries are now seeing data science as a critical enabler of their success.

Moreover, we are seeing the success of data science become a CEO-level issue. More and more, CEOs want to understand what Domino can do for their company.

The $27 million will allow us to accelerate all of this. We will use it to scale engineering so we can build out a wider-array of product features, to expand our sales footprint to New York City and London, and to grow our marketing efforts so more people understand the power of data science and of Domino.

All of this effort will move the world closer to what we imagined when we founded Domino in 2013. As we’ve written before, we envision a world where predictive analytics is at the center of the enterprise. That’s exactly what we see happening.

We see more companies investing in quantitative research and data science as a core organizational capability. As that work moves closer to the heart of the business, it’s being done more collaboratively. Companies are more concerned than ever about compounding their knowledge, and especially in regulated industries, there’s an increasing awareness that data science work needs to be auditable and reproducible. This is the exact world Domino envisions, which is both gratifying and thrilling.

If you’d like to learn more about how Coatue is using Domino’s platform and why Domino has been so valuable to their quantitative research team, you can read more about their work.

Now back to the fun part of building this business.

Nick Elprin is the CEO and co-founder of Domino Data Lab, provider of the open data science platform that powers model-driven enterprises such as Allstate, Bristol Myers Squibb, Dell and Lockheed Martin. Before starting Domino, Nick built tools for quantitative researchers at Bridgewater, one of the world's largest hedge funds. He has over a decade of experience working with data scientists at advanced enterprises. He holds a BA and MS in computer science from Harvard.

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