 Welcome back to theCUBE's coverage of women in data science 2023, live from Stanford University. This is Lisa Martin, my co-host is Tracy Zhang. We're excited to be having great conversations all day, but you know, because you've been watching. We've been interviewing some very inspiring women and some men as well, talking about all of the amazing applications of data science. You're not going to want to miss this next conversation. Our guest is Gabriela de Kairaz, Principal Cloud Advocate Manager of Microsoft. Welcome Gabriela, we're excited to have you. Thank you very much. I'm so excited to be talking to you. Yeah, you're on theCUBE. Yeah, finally. It's like a dream come true. I know and we love that. We're so thrilled to have you. So you have a ton of experience in the data space. I was doing some research on you. You've worked in software, financial, advertisement, health. Talk to us a little bit about you. What's your background in? So I was trained in statistics. So I'm a statistician and then I worked in epidemiology. I worked with air pollution and public health. So I was a researcher before moving into the industry. So as I was talking today, the weekly paths, it's exactly who I am. I went back and forth and back and forth and stopped and tried something else until I figure out that I want to do data science and that I want to do different things because with data science, we can, the beauty of data science is that you can move across domains. So I worked in healthcare, financial, and then different technology companies. Well, the nice thing, one of the exciting things that data science, that I geek out about and Tracy knows because we've been talking about this all day is just all the different, to your point, diverse, pun intended applications of data science. You know, this morning we were talking about, we had the VP of data science from Metta. As a keynote, she came to theCUBE talking and really kind of explaining from a content perspective, from a monetization perspective. And of course, so many people in the world are users of Facebook, it makes it tangible. But we also heard today conversations about the applications of data science in police violence, in climate change. We're in California, we're expecting a massive rainstorm and we don't know what to do when it rains or snows. But climate change is really, everyone's talking about it. And there's data science at its foundation. That's one of the things that I love but you also have a lot of experience building diverse teams. Talk a little bit about that. You've created some very sophisticated data science solutions. Talk about your recommendation to others to build diverse teams, what's in it for them? And maybe share some data science project or two that you really found inspirational. Yeah, absolutely. So I do love building teams. Every time I'm given the task of building teams, I feel the likeiest person in the world because you have the option to pick like different backgrounds and all the diverse set of like people that you can find. I don't think it's easy. Like people say, yeah, it's very hard. You have to be intentional. You have to go from the very first part when you are writing the job description through the interview process. So we have to be very intentional in every step. And you have to think through when you are doing that. And I love like my last team, we had like 10 people and we were so diverse. Like just talking about languages, we had like 15 languages inside a team. So how beautiful it is, like all different backgrounds. Like myself as a statistician, but we had people from engineering background, biology, languages and so on. So it's like, yeah, like every time thinking about building a team, if you want your team to be diverse, you need to be intentional. That is the, I'm so glad you brought up that intention point because that is the fundamental requirement really is to build it with intention. Exactly. And I love to hear like how there's different languages. So like I'm assuming, or like different backgrounds, I'm assuming everybody just zigzag their way into the team. And now you're all women in data science. And I think that's so precious. Exactly. And not only women, right? Like the team was diverse, not only in terms of like gender, background, ethnicity and spoken languages and language that they used to program and backgrounds like as I mentioned, not everybody did statistics in school or computer science. And it was like one of my best teams was when we had this combination. Also like things that I'm good at, the other person is not as good and we have this knowledge sharing all the time. Every day I would feel like I'm learning something in a small talk or if I was reviewing something, there was always something new because of like the richness of the diverse set of people that were in your team. Well, what you've done is so impressive because not only have you been intentional with it, but you sound like the hallmark of a great leader of someone who hires and builds teams to fill gaps. They don't have to know less than I do for me to be the leader. They have to have different skills, different areas of expertise. That is really, honestly, Gabriella, that's the hallmark of a great leader and that's not easy to come by. So tell me who were some of your mentors and sponsors along the way that maybe influenced you in that direction or is that just who you are? That's a great question. And I joke that I want to be the role model that I never had. Right, so growing up, I didn't have anyone that I could see other than my mom probably or my sister, but there was no one that I could see. I want to become that person one day. And once I was tracing my path, I started to see people looking at me and like you inspire me so much and I'm like, oh wow, this is amazing. And I want to do this over and over and over again. So I want to be that person to inspire others. And no matter like if I'll be like a VP CEO, whoever I want to be, I want to keep inspiring people because that's so valuable. And I feel like when we grow professionally and then go to the next level, we sometimes we lose that thing that is essential. And I think also like it's part of who I am as I was building and all my experiences as I was going through, I became what I mentioned is unique person that I think we all are unique somehow. You're a rock star, isn't you? You're a rock star? Are we dropping clothes out? I'm loving this. I'm like, I've inspired Gabriella. Yeah, cause we were asking our other guests about the same question, like who are your role models? And then we're talking about how like, it's very important for women to see that there is a representation, that there is someone they look up to and they want to be. And so that like it motivates them to stay in this field and to like to start in this field to begin with. So yeah, I think like you are definitely filling a void. And for all these women who dream to be in data science. And I think that's, that's just amazing. And you're a founder too. In 2012, you founded Our Ladies. Talk a little bit about that. You, you, this is present in more than 200 cities in 55 plus countries. Talk about Our Ladies and maybe the catalyst to launch it. Yes, so you always start. So I'm from Brazil. I always talk about this because it's such, again, I grew up over there. So I was there my whole life. And then I moved to here, Silicon Valley. And when I moved to San Francisco, like the doors opened, so many things happening in the city that was back in 2012, data science was exploding. And I found out something about meetup.com. It's a website that you can join and go in all these events. And I was going to this event and I joke that it was kind of like going to the Disneyland where you don't know if I should go that direction or the other direction. And I was like, should I go and learn about data visualization? Should I go and learn about SQL? Or should I go and learn about Hadoop, right? So I would go every day to those meetups. And I was a student back then. So, you know, the budget was very restricted as a student. So we don't have much to spend. And then they would serve dinner and you would learn for free. And then I got to a point where I was like, hey, they are doing all of this as a volunteer. Like they are running this meetup and events for free. And I felt like it's a cycle. I need to do something, right? I'm taking all this in. I'm having this huge opportunity to be here. I want to give back. So that's how everything started. I was like, no, I have to think about something. I need to think about something that I can give back. And I was using R back then. And I'm like, how about I do something with R? I love R. I'm so passionate about R. What about if I create a community around R? But not a regular community because by going to these events, I felt that as a Latina and as a woman, I was always in the corner and I was not being able to participate and to be myself and to network and to ask questions that would be in the corner. So I said to myself, what about if I do something where everybody feel included? Where everybody can participate, can share, can ask questions without judgments. So that's how our ladies all came together. That's awesome. It's all about intentions. Again, again. You had that go in mind, but I wanted to dive a little bit into R. So could you please talk more about where did the passion for R come from? Like how did the good special connection between you and R, the language, like bond, how did that come from? It was not a love at first sight. No, not at all. Not at all. Because that was back in Brazil. So all the documentation were in English. All the tutorials, only two. We had like very few tutorials. It was not like nowadays that we have so many tutorials and courses. There was like, there were like two tutorials, all the documentation in English. So it was hard for me, like as someone that didn't know much English, you go through the language and then to learn to program was not a easy task. But then as I was going through the language and learning and reading books and finding the people behind the language, I don't know how I felt in love. And then when I came to San Francisco, I saw some of like the main contributors who are speaking in person. And I'm like, wow, they are like humans. I don't know. It was like, I have no idea why I had this love. But I think the people and then the community was the thing that capped me with the R language. Yeah. The community factor is so important. And it's so, at WIDS, it's so palpable. I mean, I literally walk in the door, every WIDS I've done, I think I've been doing them for theCUBE since 2017. theCUBE has been here since the beginning in 2015 with our co-founders. But you walk in, you get this sense of belonging. And this sense of I can do anything. Why not? Why not me? Look at her up there. And now look at you speaking in the technical talk today on theCUBE, so inspiring. One of the things that I always think is, you can't be what you can't see. We need to be able to see more people that look like you and sound like you and like me and like you as well. And WIDS gives us that opportunity, which is fantastic. But it's also helping to move the needle. Really. And I was looking at some of the NADB.org stats just yesterday, about 2022. And they're showing the percentage of females in technical roles has been hovering around 25% for a while. It's a little higher now. I think it's 27.6 according to NADB. We're seeing more women hired in roles. But one of the challenges, and I would love to get your advice on this for those that might be in this situation is attrition. Women who are leaving roles. What would your advice be to a woman who might be trying to navigate family and work and career ladder to stay in that role and keep pushing forward? I'll go back to the community. If you don't have a community around you, it's so hard to navigate. It's a great point. You are lonely. There is no one that you can bounce ideas off, that you can share what you are feeling or like that you can learn as well. So sometimes you feel like you are the only person that is going through that problem or like you maybe have a family or you're planning to have a family and you have to make a decision. But you've never seen anyone going through this. So when you have a community, you see people like you, right? So that's what we were saying about having different people and people like you. So they can share as well. And you feel like, oh yeah, so they went through this. They succeed. I can also go through this and succeed. So I think that the attrition problem is still a big problem and I'm sure we'll be worse now with everything that's happening in tech with layoffs. Yeah, some of the great resignation. We are going back a few steps, like a lot of like advancements that we did. I feel like we are going back, unfortunately. But I always tell this, make sure that you have a community. Make sure that you have a mentor. Make sure that you have someone or some people, not only one mentor, different mentors that can support you through this trajectory because it's not easy. But there are a lot of us out there. There really are and that's a great point. I love everything about the community. It's all about that network effects and feeling like you belong. Yeah, yes, absolutely. Because that's like coming over here, it's like seeing the old friends again. It's like I'm so glad that I'm coming because I'm seeing all my old friends that I only see like maybe once a year. Yeah, exactly. And I feel like that our tank gets replenished exactly for the rest of the year. Yes, that's so precious. I agree with that. I think one of the things that when I say, you can't be what you can't see it and think, well, how many females in technology would I be able to recognize? And of course, you could be a female technology working in the healthcare sector or working in finance or manufacturing. But we need to be able to have more that we can see and identify. And one of the things that I recently found out, I was telling Tracy this earlier that I geeked out about was finding out that the CTO of open AI, chat GPT is a female. I'm like, where are we talking about this more? She was profiled on Fast Company. I've seen a few pieces on her, Mira Murati, but we're hearing so much about chat GTP being, GPT, I always get that wrong, about being like likening it to the launch of the iPhone, which revolutionized mobile and connectivity. And here we have a female in the technical role. Let's put her on a pedestal because that is hugely inspiring. Exactly, like let's bring everybody to the front. Yes. Let's have them talk to us because like you didn't know, I didn't know probably about this, right? You didn't know, like we don't know about this. It's kind of like we are hidden. We need to give them the spotlight. Every women should give the spotlight so they can keep spiring the new generation. Or Susan Wojcicki who ran, how long does she run YouTube? All the YouTube influencers that probably have no idea who are influential for whatever they're doing on YouTube and different social platforms that don't realize, do you realize I was a female behind the helmet for a long time that turned it into what it is today? That's outstanding. Why are we talking about this more? How about Megan Smith was the first CTO on the Obama administration? That's right. I knew it had to do with Obama, I couldn't remember. Yes, let's find more pedestals. But organizations like WID's, your involvement as a speaker, showing more people, you can be this because you can see it, is the right direction that will help, hopefully bring us back to some of the pre-pandemic levels and keep moving forward. Because there's so much potential with data science that can impact everyone's lives. I always think, we have this expectation that we have our mobile phone and we can get whatever we want, wherever we are in the world and whatever time of day it is. And that's all data driven. And the regular average person that's not in tech, I think thinks about data as a, well, I'm paying for it. What's all these data charges? But it's powering the world. It's powering those experiences that we all want as consumers or in our business lives where we expect to be able to do a transaction, whether it's something in a CRM system or an Uber transaction like that. And have the app respond, maybe even know me a little bit better than I know myself. And that's all data. So I think we're just at the precipice of the massive impact that data science will make in our lives. And luckily we have leaders like you who can help navigate us along this path. Thank you. What advice for, last question for you was advice for those in the audience who might be nervous or maybe lack a little bit of confidence to go, I really like data science or I really like engineering, but I don't see a lot of me out there. What would you say to them? Yeah, especially for people who are from a non, like non-linear track, we're like going back to that track. Yeah, I would say keep going, keep going. I don't think it's easy. It's not easy, but keep going because the more you go, the more, again, you advance. And there are opportunities out there. Sometimes it takes a little bit, but just keep going and following your dreams that you get there, right? So again, data science such a broad field that doesn't require you to come from a specific background. And I think the beauty of data science exactly is this. It's like the combination. The most successful data science teams are the teams that have all these different backgrounds. So if you think that we, as data scientists, we started programming when we were nine, that's not true, right? You can be 30, 40, shifting careers, starting to program right now. It doesn't matter. Like you get there no matter how old you are and no matter what's your background. There's no limit. I love that. Gabriella, thank you for inspiring. I know you inspired me. I'm pretty sure you probably inspired Tracy with your story. And sometimes like what you just said, you have to be your own mentor and that's okay. Because eventually you're going to turn into a mentor for many, many others. And sounds like you're already paving that path. And we so appreciate it. You are now officially a CUBE alumni. Yes. Yay. We loved having you. Thank you so much for your time. Thank you. For our guests and for Tracy's young. This is Lisa Martin. We're live at WIDS 23, the eighth annual Women in Data Science Conference at Stanford. Stick around. Our next guest joins us in just a few minutes.