The second segment will require you to write SQL queries and answer a few SQL questions. I’d say that our number one goal is always improving the customer experience. Jessica Lachs, Head of Analytics at DoorDash leverages data science to improve the business. Hi Rohan. The BizOps team at DoorDash is unusual in the sense that we’re driving a lot of initiatives ourselves. DoorDash San Francisco, CA. ._3-SW6hQX6gXK9G4FM74obr{display:inline-block;vertical-align:text-bottom;width:16px;height:16px;font-size:16px;line-height:16px} 0 0. facebook twitter reddit hacker news link. When an order is placed by a customer, our first step is to figure out when to place it with the store. So I’m leading data warehousing, where we collect data from all over the place. I started focusing on data architecture about three years ago. →. Both. Here are some questions asked previously at the DoorDash Data Science interview. If you don’t have this process, my definition of something might be different than yours, so we’re talking a different language. Give us an overview of what your team is working on. All Rights Reserved, Data Scientist, Analytics (Multiple Levels), Senior Data Scientist, Analytics (Multiple Teams). As a result of their growth, they need to grow their data science team to help scale their business. You can do whatever you want because there is such a need for everything. For just prep time it’s closer to 40. Software Engineer, Data Platform. Full Time This isn’t the type of work where you sit in the corner by yourself all day. ( Log Out /  We need people who don’t get overwhelmed very easily. There are lots of ways to solve these problems, but we believe a lot of these can be tackled through machine learning. Who’s on your team, and what’s your focus? When you work at a startup, it can expose you to work on different areas in a short amount of time. How far away did she park? I also have the opportunity to grow and I’m making a big impact in the company. With infrastructure we have a culture where your performance is highly visible. The food’s cold, the merchant’s unhappy, and the customer is hangry. Partner closely with hiring managers and leaders to hire top analysts and data … Their Commitment to Diversity and Inclusion. whats great about open ended shit like this is it really allows you to flex your muscles, what interests you about doordash data? Those are just a few examples, but there are many more problems that can be solved, or at least better understood, with machine learning. I believe customer demand is only going to grow and the problem statement is very challenging. Looks like you're using new Reddit on an old browser. Which boot camp is that? Yea, it’s all available. Can you make a model that makes more money for doordash? .LalRrQILNjt65y-p-QlWH{fill:var(--newRedditTheme-actionIcon);height:18px;width:18px}.LalRrQILNjt65y-p-QlWH rect{stroke:var(--newRedditTheme-metaText)}._3J2-xIxxxP9ISzeLWCOUVc{height:18px}.FyLpt0kIWG1bTDWZ8HIL1{margin-top:4px}._2ntJEAiwKXBGvxrJiqxx_2,._1SqBC7PQ5dMOdF0MhPIkA8{height:24px;vertical-align:middle;width:24px}._1SqBC7PQ5dMOdF0MhPIkA8{-ms-flex-align:center;align-items:center;display:-ms-inline-flexbox;display:inline-flex;-ms-flex-direction:row;flex-direction:row;-ms-flex-pack:center;justify-content:center} obviously your recommendations may be sorta out there since you have limited data. It’s not really particular. I also worked on some prediction stuff of my own and then, as we hired more engineers, I moved into a manager position. Bookmark; function; I am preparing for upcoming data science interview. BizOps is querying the warehouse daily to find insights and make decisions. I have done some EDA- eg what times of day are the most orders made, do some drivers make more from tips than others. Basically, when I first joined we didn’t really have a data infrastructure. This requires massive amounts of research and problem solving with real-world data. You will be asked a few questions about projects and background related to data science. From the engineering side, people are using it to find the results of experiments. For instance, when I was at Lyft we were balancing a driver and passenger. sudo shirt is an online store featuring apparel designed by developers for developers. It’s awesome. Don’t be intimidated if you feel like, “Oh man, I don’t understand this giant chunk of the field.” It’s totally fine. We are responsible for all things data at DoorDash. It’s more like all the time. Do you have an example of a particular impact on the business of what you’ve done? At this point, you will be asked a series of questions about the techniques used. they didn't proceed with the interview process and didn't offer feedback. Obviously, diversity is really important to me. You know their business model, you know what data they have, you're expected to think of some ways to improve their business using the data, then execute. Ask yourself what's a business question you can answer. i don't think they want EDA or high-level work. Jessica Lachs, Head Analytics at DoorDash. One of the biggest draws of DoorDash is our unique selection. I’m working on the dispatch team right now, which boils down to the execution of deliveries. See who DoorDash has hired for this role . Does your post belong in the stickied "Entering & Transitioning" thread? We have both at Interview Query. By building the last-mile delivery infrastructure for local cities, DoorDash is bringing communities closer, one doorstep at a time. “If you join us, you’ll have the opportunity to be an explorer.”, And yet, as deeply as data is embedded in DoorDash’s culture, its data team is just beginning to take flight (yes, that means they’re hiring). I want to provide my team with a solid foundation. The site may not work properly if you don't, If you do not update your browser, we suggest you visit, Press J to jump to the feed. Doordash Data Science Interview. Polish your object-oriented programming skills as you may be asked to modify an existing program with OO techniques.