Domino Data Lab’s Co-Founders on Seeing into the Future
The most impactful companies in business today — from Pfizer to Netflix to Facebook — use data science as their primary engine of growth and expansion. And predictive modeling — Domino Data Lab’s specialty — allows the world’s leading innovators to peer into the future and see what they’ll need to thrive. Below, Domino co-founders Nick Elprin (CEO) and Chris Yang (CTO) discuss the growing fields of quantitative research and machine learning, the power of iteration, and how understanding customer needs can lead to the next big success.
What does Domino Data Lab do today, and how will that change in the next 5–10 years?
Chris: Domino is a data science and machine learning platform that helps some of the world’s biggest organizations build and run their models more effectively. AI and modeling are becoming more and more important to how companies operate, and we think Domino can be at the core of that shift. We’re already working with big companies, and our ambition is to serve more and more of the market. We hope to spread predictive modeling across the world.
Nick: We want Domino to become synonymous with the whole discipline of data science and machine learning, similar to how other legendary companies come to stand for the type of work that they support. I often talk with candidates about what Workday is to HR, what GitHub is to software engineering, and what Salesforce is to sales teams and CRM. If we do our jobs right, then in five to ten years, Domino Data Lab will be that for data science.
How did you decide to found Domino? And how did decisions you made early on influence the trajectory of the company?
Nick: Chris and I both worked at Bridgewater — a very advanced quantitative asset manager that relies on data and models to make decisions and manage money. Right out of college, we were immersed in understanding how to develop, deploy, and monitor predictive models that are making high stakes, critical decisions. We learned a lot working there — every six months I would reflect on how much more I understood about data science and quantitative research. But at a certain point, I felt like my learning and personal growth were plateauing. I also wanted to make more of an impact on the world. So, part one was us deciding to join forces and create a startup. And part two was deciding what that startup would be.
We asked ourselves, “What do we know a lot about, and where do we have unique insights?” We concluded that we knew a lot about enabling advanced quantitative research teams. So then we had to see if there was a market opportunity. We interviewed around a hundred data scientists and asked them, “What are your problems? What are your pain points? What’s hard about the work you do?” Those conversations helped us develop the idea for a product we believed could improve how data scientists work.
Chris: Bridgewater was so far ahead of the game that working there felt like seeing and feeling what the future would be like. One of the virtues of having lived in the future is you can look back and think, “Oh, we were doing that a crazy way.” So our experience influenced how we grew Domino, because we already knew exactly what we wanted to build; it seemed self-evident.
We believe in rigorous, analytical thinking, in all contexts. I remember a meeting we had before we dreamed up Domino, when we were still experimenting with ideas in my living room. One of us said, “Hey, is this thing we’re doing any good?” And after some thought we agreed, “No, this is bad, this is not going well.” As a founder it’s easy to fall in love with your ideas, but you also have to be honest with yourself. So we agreed to move on and then we had to figure out what idea to pursue next. That moment stands out to me as the beginning of a key cultural value at Domino, the importance of self honesty and self-assessment.
Which other values guide your work?
Chris: Understanding our customers and delivering what they need is the core of our business. We built our first prototype in four weeks and immediately went back to the data scientists to ask them what they thought. We listened to their feedback, and thankfully, some people even started to use our platform. We kept that rapid feedback cycle going — asking if our work was useful, then taking feedback and using it to improve. I tend to be data-driven in that way.
Nick: A lot of our ethos has to do with humility and low ego — we’re not concerned with being right or wrong. For us, debate and discussion are collaborative, not adversarial. We often ask each other, “Hey, why do you think that?” Or we say, “Here’s where I disagree.” But it’s all in the spirit of testing and strengthening our ideas. We both strongly believe in the power of iteration. Launching early and being open to criticism is the fastest way to improve your product.
What business challenges are you focused on right now?
Nick: I think of the business broadly in two halves: There’s product and then there’s go-to-market. On the go-to-market side, we’re transitioning from doing things through genius and heroics to doing things at scale. So we’re asking ourselves how we can scale and systematize. We plan to double our Sales team in the next 12 months, and we need to build more process, methodology, systems, and training to make that work.
On the product side, especially with R&D, it’s more like a creative art problem; we need to focus more on innovation than incremental improvement. The next year for us is about making a couple of big bets to really leapfrog the market again with major innovative product development. And we have a bunch of exciting plans for doing that.
Chris: This year in particular, we have so many of the raw ingredients in place for product development. I’ve been thinking a lot about how to create a larger system to support more rapid product development, and that may mean creating super tight Product and Engineering teams who can become company — and world — experts on a specific set of use cases. We’re not going to get too far if only one person is thinking of interesting things to do. And so a big chunk of the challenge is creating a situation where lots of really smart people can be iterative and take risks to come up with innovative stuff.
How is working at Domino different than working at other companies?
Nick: Domino is far enough along that we don’t have the risk profile of an early-stage startup. We have a strong product market fit, ample funding, lots of customers, and plenty of revenue. It’s clear there’s a need for our product. But we still enjoy a lot of the fun things about being a startup. We have to move with a fast pace and a sense of urgency given the competitive landscape, and that’s appealing to people who thrive in a high-energy environment.
“If you’re self-reflective, analytical, and willing to grow, then we can support you.”
Chris: We focus a lot on personal growth at Domino. We want to work with people who are motivated by the idea that their work matters. And we have so much to do and need to move quickly, so every role is essential to our company’s success. Our emphasis on the iterative process also relates to the personal and professional growth of our employees. We encourage our employees to stretch, and to know that sometimes they’re going to fail. If you’re self-reflective, analytical, and willing to grow, then we can support you.
We are a company of 200, but our platform supports companies of thousands. That’s where the impact comes in. Our teams are small and you get to know everyone, but your contributions can have a ripple effect far beyond the world of Domino.
How do you think about diversity and inclusion at Domino?
Chris: Our core values center around being analytical and data-driven, which aligns with having interview and promotion processes that are fair and equitable. But the reality is that we’re biased, even when we don’t want to be. So how can we bring in the right people to help make sure we’re designing a fair and equitable system? That’s a challenge we’re facing now. We’re definitely aware that we’ve got a lot of tall, white guys in the room, and we’re working to diversify our pipeline.
Nick: We’ve got recruiters thinking about deliberate strategies for diverse sourcing, and we’ve built more rigorous assessment plans. And we also value diversity of thought; we’re working to create an environment where people of all different styles and personalities can be successful.
What are you most looking forward to as you head into 2021?
Nick: We’re in one of the most dynamic and hottest spaces in the world right now. Machine learning and data science are part of the biggest disruptive trend in business and technology in probably the last 50 years, and the industry is still in its infancy. We’re working toward our vision of a continuous loop where our customers are doing research, building models, deploying those models, and then refining, retuning, and redeploying in a single, integrated platform.
Chris: We have serious customers in a variety of fields — and they want to see our work immediately. For example, there’s a pharmaceutical company that uses Domino, and they’re using our platform to do COVID-19 research. With that kind of demand, it’s imperative that we ship innovations as quickly as possible. We want to continue making a significant impact. Helping our customers is simple; we just have to keep leaping into the future.
Interested in joining the Domino team?
Reach out at careers@dominodatalab.com or check out our careers page to learn more.
