 Good afternoon tech community and welcome back to Stanford University. We're here at the data and women, or data, women in data science, wow my dyslexia is having a moment. We're celebrating the neurodiverse and women here on International Women's Day. At the Women in Data Science Worldwide Summit here, my name is Savannah Peterson, you're watching theCUBE. I am so excited for our two guests we have left this afternoon. One of them works at a company I am 100% confident you've heard of. The company is Pinterest and our next afternoon guest is Hannah. Thank you so much for being here Hannah. Yeah, my pleasure, it's such a great day. You can feel the energy buzzing here. I know, that's the best part of being here in person. Have you been to an event before here? I actually know, this is my first time. Me too, and I will say it's such a nice intersection of energy and excitement paired with a very nice calm and empowering tone. I don't feel the kind of stressy, buzzy. You can tell there's not a lot of sales people here, no offense to the sales pros of the world, but it just feels like everyone's here to learn and to empower and it's very cool. Yeah, perfect, totally. So you are at Pinterest, first of all tell us a little bit about your job and then I want to talk about your journey and get there, but what do you do for Pinterest? Yeah, definitely. So I am currently a Data Science Director at Pinterest. I am responsible for basically like all the pinner engagements that we call our core users, dear pinners, right, like you pin, pinners. So my team, my orgs, is responsible for understanding basically all the core apps that you are looking at, like all the different surfaces, search, home feed, close up, shopping, behavior. So like anything, like the core user experience is what my team is responsible for. So safe to say that Data Sciences is very core to Pinterest's business and success I would imagine. And probably a day one priority too. So how did you get into Data Science? Great question. So I would say I've always been a math nerd. That's great. Don't get shy when you say that, that's hot. No, not shy, proud. Yes. I love nerds, I'm a proud nerd. This is like best, we gotta get that pride going, exactly. So I, even when I first started school, I love math. You know, I've always been solving problems, always curious. I just like from day one in school, I've always like math problem, asking a lot of questions. It's a very natural transition. Like I did math and econ at MIT. So like also very mathy nerdy fields and then out of school, Data Science. I mean, I started Data Science even before it became Data Science is a term if you think about it, right? Like the field dated back then started, it's about solving problem. How do you use data and math to solve problems around us to make everything better, the world better? So yeah, it was a very natural transition to me. I actually started out in finance and I was like, well, I want to do more math. So I switched into like Data Science and Data Analytics and yeah, that was my journey, how I got into tech. And you know, the Bay Area is the best place to be able to experience all of that energy and to be able to get in a lot of big data. Yeah. Absolutely, yeah. Silicon Valley is definitely not dead. Was there a moment when you were a little girl that you remember getting particularly excited about math? That's a very interesting question. You know what, I always solve so many problems. I think like even there was a moment when I remember I had like my eyes got hurt so I couldn't see for like a week. Oh my goodness. I was in the dark room, couldn't see and I was so bored. I was just like, close my eyes and I solved math problem in my head. Amazing. That was the moment when I knew that, well, you know, this is my life. This is like whenever even the sort of the worst moment at that point when I was sick and couldn't do anything, couldn't even open my eyes, couldn't... I was like so much craving for a piece of pen and paper so I can solve problems. I know it sounds really... It sounds amazing. It tells me how incredible your brain is, is how I hear that. Yeah, but I was just like imagining all the shape in my head and I was like, oh, I solved it in my head. That was the moment when it clicked and I was just like, yeah, this is what I want to do. Wow. And how old were you when that happened? I was in like, I would say eighth grade, so. Oh my goodness, yeah, so pretty young. That's so... I love that I can see you. That was a great description of that moment. I can see you in this very scary moment, probably with impaired vision. But then the thing that your mind does to keep you stimulated is to solve math problems. I love that. It's very clear that you've ended up in the right career path. When you started working through your academic career, Pinterest may not have even been around yet. What is it that attracted you to working at Pinterest specifically? You know what Pinterest is? Like something that we're always so proud of is we are the positive corner of the world. You really are. Yeah, we're here to like... Totally something to be said for that. Yeah. It's so amazing, like speaking of the energy of this conference, when they're talking to all the conference folks who they came to me and like, oh, you all got Pinterest. I love Pinterest. And I love talking to people, the pinners. And they're like, what do you use Pinterest for? And they're like, look at this. I'm like inspired. I use this to like set my mood board and just like all of these beautiful pictures. It makes just my life better. You know, like people always talk about like how social media you are mildly scrolling with a Pinterest people are very mindful. Like it's a Zen place where you're there to like really the positive corner of the internet. I would say so. So that's why I was so into Pinterest. And they also use it to plan for my wedding during COVID. So it's like, perfect. Yeah. Well, it's important to be a user of the product to know how to understand how to optimize it best. I do really like what you just said though, a positive corner of the internet. A, I don't think we have enough positive corners of the internet. B, when you look at social media companies and Pinterest was very much a part of that early era of them once we were around kind of the Facebook, Twitter era rising around the same time as Instagram. You don't see the malice and the toxic behavior on Pinterest. Is that something that, and I wasn't planning to ask you this, but I have to now, is that something that Pinterest is, I'm sure you're proud of it, but is it something that the company focuses on? Is that something that's a part of your data science approach? Yeah, definitely. I think like data science for good and data science for social impact is something, but I think we don't talk enough about, we can do so much good with data. I mean, we could also do much bad with data too, but when you're my fault of the power of data, the power of what you can do with the implication of the models of the insights you bring to the table and how does that feel all the decisions and knowing and being aware of all of that is so important. So I think as a company, we very much care about, like I said, I think this is the model, I didn't even have to think about it, it's just like the positive corner of the internet is what everyone thinks about and care about at the company. So being able to do data science in a company like that is very exciting. Yeah, and I bet it makes it so you can sleep at night. Yeah. You're not doing content moderation at Metta, you're looking at wedding dresses. No comment on that one, but yeah. Were you, I mean, I'll make that comment as an analyst. Were you using Pinterest before your wedding? I was starting using it for like organizing ideas for my house, but like really intense, intense using it was when I like the wedding and then when we got the house and you were like, oh, what should I put things and like all these beautiful ideas I want to put. It's just like building your dream life, you know, like putting your dream together. Yes. It's how I see it. You know, it's not just like a moment in time when you sort of, my list for getting, like trying to run away from your real life here, you putting your real life in there and making it better. So that's that's why I love butter. I think that's really well said. You're curating and you're staging your dream life. Yeah, exactly. I mean, twist my arm, that sounds pretty fat. You're gonna make me want to use Pinterest again. I haven't used Pinterest in a hot minute, but feeling actually a little inspired about that. And I love thinking about it as a positive corner. Do you, are there anything, is there anything you have to do as a data science at Pinterest to combat a negative or nefarious behavior? I mean, there's a lot of things. I'm actually not work in those teams and I don't know what I could say. Yeah, well that's, I mean, that just means that a lot. The team that we're working on, the team that I'm working on is very much focusing on like how do we bring the most positive and like beautiful experienced users? Well, if you're looking at the home feed, you're looking at the search behavior and most recently we're looking at shopping. How do we make it all coming together? Right, like all of the behaviors, all of the intent, like people are here to shop, people are here to dream, to plan, to build a life, like how do we put all of those in a very like, streamlined way, like seamless way? People don't have to think. Yeah, and how can you predict or be intuitive to their desires and needs on the platform, which could vary by visit. Maybe sometimes I do want to shop, sometimes I want to curate my dream wedding list or whatever that might be. Exactly, like you don't want to push things in front of people that like they don't want to see, really, you want to make it like basically optimized with people's happiness to think about it, that way, yeah. What it is really interesting too, I'm wondering if you work on this team and obviously if you don't, it's okay, but I'm curious, so it's like an Insta for example, the algorithm, I've been going through some grief and then recently I've had some positive things happen in my personal life, so I get hit with a very unique cross-section of both sad and very happy, do you have to be, are you a part of the crew that weighs what people are served when they arrive to Pinterest on a given day? Yeah, so I think like, so we have the search, we have the search surface and we have the home fee surface, right? So home fee is when you just go in and you just like browsing and there's no particular search term that you're looking for and the search one is like, let's say I want, I don't know, like wedding ideas, outfit idea or like dinner party, work outfit, so those are two different use case people have, sometimes people come in with very specific ideas they have in mind that like, hey, I want to build up my wardrobe for the spring, so that's the search one and the home fee one is when, basically like based on people's previous behavior to serve people what they would like and the most suitable for them is what we see it on the home fee. Nice, yeah, so kind of balancing what they may be coming to do looking forward versus what we know is going to be something they've always enjoyed. Interesting balance of predictive and existing data there too, actually, which is rad. We've got a lot of really empowered, awesome women in data science here in this room, yourself included. What would your advice be to a woman thinking about embarking on a career in this space? Yeah, I love this question because I mean, I remember years ago when I was that, when it was that woman, right? Like I always wish, oh, I would love to talk to people who's ahead of me in their careers and what, so now I'm thinking about, well, like me at that point, what would I tell them? Or like talking to all the women, very inspiring women that I meet today, what do I tell them? I would say, you know, do it. Like, I know it sounds like a recording or like follow your dream is the only thing I can say, like you can't plan everything in life. Like there's certain thing, obviously, like you maybe plan like two years, three years ahead, but not everything's gonna happen like you exactly plan. So I think putting in a lot of effort, doing, do a lot of due diligence, work hard, ask for things, ask for support. Yeah. We don't do that enough, I feel like as women, we don't, we- I totally agree. We need something, we ask for it. Like you miss 100% of the shots and you don't tag, right? I can't get what you don't ask for either. No one's gonna know you needed it. Yeah. Exactly, and like ask for even things like, sometimes people are like, I don't know what I want. Talk to people. How else would you know what you want until you talk to people? Like that's the most basic question, basic advice I give to folks who are in school and when they're like, oh, what are the tracks of data science? And I'll be, I would tell them, hey, I can tell you, like do some basic search on Liza, like few different tracks, like data engineering, data analytics, machine learning, inference, read some blogs, read about it, do your research, and then talk to, go to these conferences, talk to people, ask them about what's the day-to-day looks like, get a sense of like, oh, do I want to be that person? That person sounds awesome, their job is amazing. Or they're like, nah, I don't really want to do that. That's both of that, it's really good to know because you don't want to like, sort of chasing what all of your peers are doing because it's sort of like the train are hot and you get into it and you just turn out you really don't like your day-to-day. So I think talking to these people, like you all have such a great network. I think like nowadays, you have like alumni network, you go to conferences, talk to them and get a sense of what it's like, what you want, find out what you want first, and then get for advice. I feel like I always love to help people know- Likewise, yeah. Like know the right questions to ask. I think it's very important to help them to help you. I think that's great advice. And especially, I just want to double down on what you just said. So many people think about work as a job title or as perhaps the cream at the top of that layer of what that job really looks like or the rest of the iceberg underneath what it is. People think of a lawyer and they think of being in a courtroom and doing trial law, which is actually a fingernail of the body of what a lawyer does or what most people do. It's the same thing here. I mean, we've got opportunities where you can, you won't know unless you talk to someone who is a data scientist until talking to you about how you're thinking about curating the home feed for example or the decisions you're making or whatever that might be. You won't know what your day is gonna look like and we spend so much time working. You don't want to spend your day doing something you absolutely hate no matter how much money it makes. And that's just the reality, it'll get you anyway. What is your advice for the allies in our world empowering women like us in our space? Yeah. I think, I love it, you know, because of the years ago when I started thinking about empowering women, I focused so much on what should women do. And I think equally a part of it is how should we educate allies to do and help us too, right? It shouldn't be put all the responsibility on the women to put themselves out there to ask for help. I think it's allies, there's so much we can do. I would say that like talk to the women that you care about in your life. Understand the struggles, right? Like a lot of the time it's hard to put, like in yourself and other people's shoes, right? It's so hard to know that okay, maybe like as a man, it's so natural, you can't think about it. So just talk to the woman in your life, understand what you need, ask how you can help. It's like if you don't know, just ask. I think nowadays sometimes people are just like worried about it and just like not sure what to say. Agree. Yeah, like just have good intent. That's all I can say, right? I wanna make the barrier to help, it's for allies to help lower, right? So... And clearer. Yeah, clear, exactly. Yeah. Yeah, so I think as women, I'm doing my best to tell them what I need, but at the same time, I encourage them to like, hey, if you don't know, just ask. There's no problem. As long as you have good intent, it's all good. Yeah, yeah, yeah, the best amongst us are not gonna get mad at you for asking to help. And frankly, you brought up another good point there, which is just listen. Yeah. Listen with the goal of talking. Listen with the goal of listening. Yeah. And learning a bit. That's very well said. Yeah. I love it, those were great pieces of advice. All right, Hannah, last question for you. It is International Women's Day and we are here to celebrate the women in our lives and the women on this stage. Is there anyone you'd like to give a special shout out to today? Yes, there is. My mom, I know she's not watching this as she's in Vietnam, so. She'll be watching it tomorrow. Yeah, she'll be watching it tomorrow. Hi, mom. Yes. Hi, mom. Sending love from Stanford. Yeah, yeah, I'd love to say thank you. Shout out to my mom. Without her, I wouldn't be here. She's a beautiful, super smart woman who has inspired me to, nothing is impossible. Literally, right, like, I'm here today where I am today is because of her, so. Thank you, mom. That's beautiful, Hannah. And clearly, you have followed her advice and empowered yourself to be an absolute baller. Very proud to have you today on the show. Thank you so much for being here. Thank you so much. This is such a joy. And thank all of you for tuning in to theCUBE's all day coverage here at Women in Data Science Worldwide Annual Event at Stanford. My name's Savannah Peterson. My heart feels full and big and I hope yours does too. Thanks for tuning into theCUBE, the leading source for baddies in tech.