Building a world-class data org | Jessica Lachs (VP of Analytics and Data Science at DoorDash)

**Lenny Rachitsky** (0:00)
So you've built one of the largest and most respected data teams in all of tech.

**Jessica Lachs** (0:04)
For me, analytics is a business impact driving function and not purely a service function. Not just answering the why, but answering the what do we do now that we know this?

**Lenny Rachitsky** (0:15)
One of your colleagues told me that you're incredibly good at defining metrics.

**Jessica Lachs** (0:19)
Retention is a terrible thing to goal on. It's almost impossible to drive in a meaningful way in a short term. Ultimately, you want to find a short term metric you can measure that drives a long term output.

**Lenny Rachitsky** (0:32)
You mentioned the early team had built extreme ownership.

**Jessica Lachs** (0:34)
Yes, you are a data scientist, but your goal is to figure out what's happening. And if that means that you're gonna pick up the phone and call customers, then that is what you're gonna do. So roll up your sleeves.

**Lenny Rachitsky** (0:48)
Today, my guest is Jessica Lachs. Jessica is Vice President of Analytics and Data Science at DoorDash, which has built one of the biggest and most impactful data teams in tech. She's been at DoorDash for over 10 years and was the first GM at DoorDash responsible for launching new markets. Previously, Jessica founded GetSimple, a social gifting startup, and began her career in investment banking at Lehman Brothers.
In our conversation, we go deep on how to build and scale your data org, including why a centralized org model is so effective, what to look for when hiring data people, how to pick the right metrics for teams to align incentives and drive the right sorts of outcomes, examples of how the data team at DoorDash has helped the business make better decisions, a bunch of great stories about the early days of DoorDash, and a ton more. If you enjoy this podcast, don't forget to subscribe and follow it in your favorite podcasting app or YouTube. It's the best way to avoid missing future episodes and helps the podcast tremendously. With that, I bring you Jessica Lachs.
Jessica, thank you so much for being here and welcome to the podcast.

**Jessica Lachs** (1:55)
Thank you so much for having me. I'm very excited to be here.

**Lenny Rachitsky** (1:58)
So you've built one of the largest and most respected data teams in all of tech. I've heard from a number of people that look to you for advice when they're trying to build and scale their data teams. And then DoorDash in particular is an incredibly complex business. There's three or maybe even four sites to the marketplace. There's this operational elements. From the outside, it just feels extremely complicated and wild. I imagine from the inside, it's even more wild.
Let's talk about some of the things you've learned about building and scaling the team. You have a fairly contrarian perspective on how to structure data teams. This is referenced when we had Elizabeth Stone on the podcast too. She approaches data the same way. So I'd love to hear just your take on how to structure data teams within companies.
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