 Good evening data science nerds and welcome back to Stanford University where we're here celebrating International Women's Day with live coverage all day long of the Women in Data Science Worldwide Summit. The event's been going on for nine years and we've been playing a role for more than half of that. Very excited to be here. My name's Savannah Peterson. You're watching theCUBE. Our last segment tonight is a very exciting one. I am thrilled to welcome to the show. Amiko, thank you for being here. Thank you for having me. Have you had a beautiful day today? You holding up all right? I mean, it's a beautiful day outside. Yeah. It's a great company here, so I can't complain. Yes, and you've been a part of this community for a little while, correct? A couple of years now, yeah. Yeah, so what does it mean for you to be here and get to hang out with all of your peers? You know, like on an everyday basis, like, don't really interact with other women's really like. I bet. So it's kind of, I have one other female coworker, but that's it. So it's kind of nice to see a room full of other data practitioners. It's refreshing. Yeah. Yeah, I mean, we look at the data. 20% of students, only 10% of decision makers in data science are female. You and I both know the odds are not necessarily in our favor when we look around the room. So it is great to be absolutely surrounded by this brilliant group of people. You are a data scientist at V2 Solutions. Just in case the audience isn't familiar, what is V2 Solutions do? It's a service provider. So like we provide consulting, also like just services in digital transformation aspect of it. Like I'm more in the data science aspect, obviously. I primarily work with clients and primarily one client in real estate and I do a lot of their data. Like I meet their data needs, whatever that may be. Can you give us some examples of the types of data needs? And it doesn't have to just be the real estate folks you're working with, although if you can disclose about that, that would be awesome. What are some of the data needs that people come to you with? Yes, like a lot of it is honestly, well we need these reports, but like they don't have the technical skills to like put together the data from that not necessarily are in like one database, right? Like it could be in the database, it could be somewhere else. So like they don't necessarily know how to put it together to make the report. So like that's where I come in like, yeah okay I could do that for you and like just make that happen. So I see a lot of that and I see a lot of like also like data pipelines in order to make that those reports happen, right? Like they need to happen so. And they need to be clean data. It's got to be, yeah. I mean I bet you're helping people evaluate whether or not they even have a solution potential with the current data they have existing. Yeah and like a lot of it is also like help, you know, a little bit of consulting in a sense that like maybe you should think about this, right? Like I mean at the end of the day it's the client's decision whether they will take that or not but I feel like that's part of my role like make suggestions so that you know they may think about it. I bet you're doing a lot of education as well. I hope that. Yeah. Well you're probably teaching some of your clients about how to even think about these problems and what's possible. Yeah I think so. I mean like I hope that I'm making a difference in you know with my work. Yeah. Making things better like for what's to come for the companies. It certainly sounds like you are. You started in the lab. Correct. Doing research and lab work that you shifted a little bit in your career. Tell me about how you approach that how that currently plays into your existing role. Yeah so like I was a lab scientist research in academia. I built my career, my identity essentially in that so. What were you studying when you were doing that or what were you researching? Microbial evolution. Wow. And genetics like yeah. Yeah. So very niche obviously like different when I in my latest like the last lab position I had I always told people that I studied once come. Yeah. Well I mean. It is what I studied. But anyway like the research was I was great. I loved it but you know like I didn't love all aspects of it and what I started thinking about when I decided okay I want to move away from this lab setting. What can I do next? It was like identifying what I liked about the research and I came out with the data analysis portion of it. Was it challenging for you to pivot? I think yes. I think a lot of it is one is psychological right? Like I said I built my identity. So letting go that is a process on its own. And also like convincing folks that I can do the work. Not coming from like a straightforward background I suppose and like having a career essentially before like applying to like kind of junior roles and like convincing people that yes I still want that. Right. And that it's transferable and that you're willing to skill up. Has that been a worthwhile journey for you? Are you glad you made that shift? I am like it's been, I think a lot of it is like when I stayed in this lab for so long I think it's start to become a little bit of a repetitiveness that becomes a little bit not as fun anymore. So by changing it's like a big change obviously. Yeah, that's what I mean, it's huge. Not everybody has to do this drastic change obviously. Yeah. But I did. But what I like about that is that you can always make the change. You're not saying it has to be drastic but the point is you would already to your point made a career studying Ponskum. You were established and known and had a reputation around that but you wanted to tweak it and become more creative. Was there something about digital transformation that drew you? How did you end up at V2 Solutions? So that was a little bit more certain with this. I was like actually participating in a hackathon and I met the manager that eventually hired me during that hackathon. I was just, he was part of the team that I was in and we just chatted obviously like what do you do? You do these projects. And I somehow made an impression on him. He kind of kept tabs with me over the few months later and eventually he asked me if I'll submit my resume. So. I mean it's pretty cool. The reason I bring that up is it shows if you show up and you participate, you're there on your free time ISM doing a hackathon and you meet the right, you never know who you might meet and what doors that might open. Yeah, I mean I've always, during that time I was trying to network a lot and I kept that in my head. I never know who I'm gonna meet. Take every chance you get. Talk to everybody that will talk to you. And even the ones who won't know. I mean I can't really twist somebody's arm to talk to me but like this is also like in the hybrid pandemic so people are actually pretty willing to talk to others on Zoom and. Second advantage of the opportunity. Yeah. So whenever they say yes, like I'll talk to you even for 15 minutes I was like yes, thank you. I'll take that. Yeah. So I talked to a lot of folks during that time and just trying to also like I said I come from a biology background. I didn't know where I fit in the data science world necessarily. So like also exploring a little bit of what's out there. Like in that sense like I'm a, I'm totally naive of what can be possible, right? Like I don't actually know. So there was like a two-fold like. Yeah. I went on job but also at the same time like just a general curiosity. What is out there? What draws my attention? It's also drives like you know what other things I want to learn later. Oh yeah. And you bring up a really good point. You don't know what you don't know and your curiosity is what was able to drive you to discover. Where is there any, now I'm just curious, speaking of curiosity, is there anywhere, is there anything you're curious to learn next? Oh, you know, it's a good question. Just I have too many interests I think. Well, I suffer from this as well. But give us a couple of them and they don't have to be related to your job. I'm just curious as a human. So just because like I was looking at the talks today and like some of those, I do care a lot about using data for good causes and those kind of things really draw my attention and those vision projects that they were using for detecting trafficking that was like really, really interesting. Yeah, yeah. We talked to them earlier today, actually. Nice. Yeah, yeah. Fascinating. Yeah, it's completely fascinating and it's like also a hard work that. You're getting data on a population that is people are trying to make invisible. Right. It's an extraordinary challenge. Yeah, so I don't necessarily have to go like to vision because I'm not a vision. That's not my background. I'm more of shining the actual data. Yeah. Into dimensional data sets. Like those kind of things are like what my specialty is. Like that's what I've always worked with, right? So, but it kind of makes me think it's like, oh, how can I use my skills to help those causes, right? Yeah. Those are the kind of things that like draw my attention. It's like, I want to generalize it because like in terms of technology, there's so many things I want to learn. I think that's a great way of pulling it together though. I mean, we also talked about the UN human security goals and a lot of the different sustainability initiatives that folks here as well as around the world are all committed to to your point. And when we're sitting here in the heart of the Silicon Valley, there's a lot of brain power here and it doesn't all go to tech for good. Right. And that is I think one of the great misses to a degree of what we do here. And I love that you're plotting because I can tell from just talking to you for a few minutes and even your past curiosity is going to drive whatever happens next. And so even if that's working with the clients that you currently have with your job, you can help them to make good technological decisions, not just for the efficient for the organization but using tech for good. That's more inclusive and thoughtful. Yeah, it's like a lot of it is like how to, this is kind of how I see a little bit of my role now and like hopefully into the future as well, like however I progress, is like helping decision makers make decisions with the data. But in a way that I feel like it shows, well, it's a for-profit company, obviously. Profit is like what's most important but also like show like, okay, this is the profit that you could drive but are there any consequences if there's that? Like I want to be able to have the courage to bring that to the table as well. Yeah, do you think being a data scientist requires a level of bravery? Because sometimes I feel like you might be aware of a truth that people around you might not want to know. Yes, I think, yeah, in that case, yes. I think also, I tend to be like very persistent and patient in convincing people who might slowly. I could see this in you. Yes, just not going to take no for an answer and resilient, yeah. Well, it's more like eventually like, I know you're going to change your mind if I say it enough times. Right. It's not necessarily like, I'm not like going to be yelling, that's not my personality. But like it's more of a, I'm going to bring him up every chance I get if it's appropriate. Yeah, no, I think that's fantastic. We've got a lot of very empowered women in data science here in the building today. 400 plus, I believe. What is your advice for a woman of any age who might be considering a career in data science? You know, like you bring up a point in curiosity. I think it is kind of keeping that curiosity and kind of willingness to take any challenge. I feel like research, that research for me, it's what kind of gives me that power a little bit. Like, you know, not being comfortable with unknown a little bit because like in research, like, yeah, nobody knows what I'm doing, right? Like, I need to figure it out. Right. And like, for me, that is a strength. And if somebody out there feels like, oh yeah, I'm not afraid to try something new. I think that's a power to you. Yes, absolutely, love that. Bring the curiosity. What's your advice to the allies in our network looking to empower women like us? Keep them close. And encourage each other. So I'm also part of like Women in Big Data. It's a different sister organization. And I recently started as a Bay Area co-director. And so I'm trying to also, you know, help others the way I was helped during this process. And like, you know, maybe I could help somebody else like enter this world. Science has always been, obviously, I was biologist doing data science, but I feel like I always be going to be a scientist no matter where I am. Hey, nothing wrong with that. We need more scientists, quite frankly, yeah. And final question for you today is it's very clearly the end of the day. And we can see that the hall just let out. The energy is buzzing. Everyone's heading to a reception after a brilliant day of collaboration. It's International Women's Day, and we're celebrating. Is there anyone you would like to give a shout out to or say thank you to that's helped you on your journey? Oh, there's a lot of people, but I just say my mom. I feel like she always encouraged me to like pursue anything I wanted. Like it's not, there's never been like, no, that's a bad idea. I mean, it's like, I feel like anybody that it's out there like needs at least one person that has a unwavering belief in like whatever you're doing. It doesn't matter whether you understand it, like my mom has never understood what I've done, what I do, but. Mine doesn't either, don't worry. But you know, she still was, she was still smiling, encouraged whatever I chose to say I've made. You don't have to understand something to understand that it matters to the people you love and to tell them that you're proud of them. So I'm sure your mother is a very proud, shout out mom, shout out to my mom while we're at it. Amiko, thank you so much for being on the show. You're an absolutely fantastic guest. And thank all of you for tuning in to our full day, nine interviews of coverage here at Stanford University at the Women in Data Science Worldwide Annual Event on International Women's Day. My name's Savannah Peterson. Thanks for tuning in to theCUBE, the leading source for Enterprise Check and Bollar Women News.