Operations vs. Algorithms: Advice for scaling startups, from Opendoor CTO Ian Wong

Today’s episode is with Ian Wong, co-founder and CTO of Opendoor. Before founding Opendoor, Ian was Square’s first data scientist, where he developed machine learning models and infrastructure for fraud detection.

In today’s conversation, we cover his essential advice for how to integrate data science into your startup. As Ian puts it, in the early innings it might make sense for your startup to be operations heavy. But as you start to scale, data science becomes a critical component for running a business with longevity in mind. We dive into how both Square and Opendoor approached this transition.

Along those lines, we discuss some of the early considerations for your fledgling data science team, including the type of folks to hire for the early team, like whether to look for generalists or specialists, and how to set up your interview loops. Ian also dives into his lessons on structuring the data science function so that it’s deeply integrated with the rest of the technical org.

Next, we dive into some of his biggest lessons as a first-time founder and CTO, including his practice with Opendoor’s leadership team of doing pre-mortems to predict why something might not work. He also encourages founders to run through a bi-yearly exercise of re-writing their job rec.

You can follow Ian on Twitter at @ihat

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