>> Announcer: Live, from Stanford University, it's theCUBE, covering the Women in Data Science Conference 2017. >> Hi, I'm Lisa Martin, welcome back to theCUBE. We are live at Stanford University at the second annual Women in Data Science Conference, the one-day tech conference and we are joined by Julie Yoo, who is the founder and chief data scientist of Pymetrics. Julie, you were on the customer panel today. So welcome to theCUBE. >> Thank you. >> It's great to have you, it's such an interesting background. >> Julie: Thank you. >> Neuroscience meets engineering, or engineering meets neuroscience. I'd love for us to understand a little bit more about those two, how they're combined, and also, about Pymetrics. But give us a little bit of a background, as a woman in the sciences, how you got to where you are now. >> As you mentioned, my background's in computer engineering and I went into PhD program in electrical and computer engineering 'cause I wanted to study artificial intelligence. I was fascinated by the notion of artificial intelligence. So my research topic started in automatic speech recognition systems, building computers to decode and decipher human speech. After a couple of years, I got frustrated with just the engineering approach or statistical methods-based approach to improving the existing speech recognition systems that are out there, 'cause I thought to myself, We're trying to make computers understand human speech and mimic human function when we don't really understand how our brain works and I don't really know exactly what happens when you listen to you speak, when I listen to you speak and when you listen to I speak, what is going on? We didn't really have a good sense, so I wanted to study neuroscience. So I quit engineering and I went into PhD program in neuroscience and there, I started doing a lot of neuroimaging study, just looking at human cognition and just figuring out what is going on when people perceive and process these signals that are out there. >> And was your idea to eventually marry the two? >> I didn't really think about it that way, but it just sort of happened, as in like, my background in engineering sort of homed me into doing some of the projects that I did when I was doing my PhD and my post-doc. And while I was doing all that, I just evolved to be a data scientist without, really, me realizing I was doing everything that a typical data scientist would do. And this was even before 2008. The job title of data scientist wasn't even around then, so it sort of happened because of where I came from and because what I was interested in and as I was doing that, it just ended up being a good marriage. >> And there it was. Talk to us, tell people what Pymetrics is and what the genesis of this company was. >> Pymetrics is a platform that uses neuroscience-based games and data science to promote predictive and bias-free hiring. How we became a product was because I was going through post-doc and my co-founder was also going through business school and we were both going through the phase of, Okay, we don't want to stay in academia. What do we want to do with our lives? And at the time, we realized a lot of the career-advising tools that are out there were not scientific and they were not data-driven and we felt that there is a clear need for a tool that can actually use all these data that are out there to help people figure out what they should be doing with their lives. So we thought we were uniquely positioned to use our background in engineering and neuroscience and build a product that could actually solve these challenging problem and that's how we started Pymetrics. >> That's fantastic. You started about three years ago in 2013. So, really getting rid of some of the biases, share with us what some of the biases are. Is it test scores, SATs, MCATs, GPAs? >> There are many, many different kinds of biases in hiring process right now, I think. There is a preconception of what an engineer should look like and I think that plays a lot. And when you do going to an interview, how you look and how you dress, it adds to the bias. There is ethnic bias, there's gender bias, and there is bias based on test scores and what school you went to. So we want to remove ourselves from that and really get down to what kind of person you are and are you really... I guess, have the right set of skills to succeed in certain job functions. We do that by measuring, instead of taking your subjective answers from questionnaires, we do that by objectively measuring your behavior and these games are based on neuroscience research so we know that they actually measure things that we want them to measure, for instance, your ability to pay attention, your risk appetite, and all those things that we think matters as to what makes you good at certain things and not so good at some other things. So we use these objective data and data science and predictive modeling to come up with predictions as to how good you will be in certain career versus some other career. >> Really, an incredible need for that. It's game-based, so it's an actual game that people will play that will help understand more of who they are as a person, their behaviors, those patterns. Tell us a little bit about the invention of the game, what was it like, who was it for? >> The games were actually sourced from neuroscience research community. We did not create these games. What we did was we actually just took them from research and medical settings and applied it through hiring. We know that these are relevant to measuring your attributes and your personality, so why not use it for hiring and career advising, because it makes sense. We're trying to measure your qualities, your soft skills and what-not, why not just use it for something that could really benefit from these sort of data. What we did do is we actually made these games, they're not really called games in research community, but we made it shorter and we made it more applicable to the things that we are trying to use if for. >> You took feedback from some of your earlier adopters who were saying maybe it's taking me too long, maybe some of the recruiters might say, they gave you some very viable feedback that have helped you optimize the products. >> Right, as a data scientist, I always think the more data, the better, but that also means that people would have to sit in front of their computers and play an hour-long battery of games and a lot of people were thinking that it might be just a tad too long and companies felt that spending 45 minutes to an hour could be a discouraging thing and people felt fatigue effect and we could see that in the results, so we ended up making it shorter. We went from 20 games to 12 games and we cut it down to 25 minutes long and I think, now, we're in the sweet spot where we do get enough data but, at the same time, we're not making it an hour long. >> Right, so this is really targeted for people coming out of university programs, whether it's bachelor's, master's, doctorate, et cetera, and also, what type of companies who are looking to hire, what's kind of your target market for that? >> I think mostly Fortune 500 companies 'cause a lot of these companies do hire in large volume, so it helps to have us go to these companies and build their models based off of their employees. And if a smaller company comes along and they only have 10 employees in the job function, then it's extremely difficult for us to build the model base off of their 10 employees, whereas if it's a larger corporation, then we can have 200 employees play and we can build the model based on their data. So generally, large corporations is our target clients. >> I'm curious, in terms of some of the data that you are seeing, that you're analyzing, are you seeing, we look at data science as a great example of the event that we're at, in report from Forbes recently that said it's the best job to apply for in 2017. We're looking at now what's going to be happening, predicted over the course of the next year, and that's a shortage in talent. Are you seeing, with some of the data that you're taking in, are you seeing things that are mapping to that, like people that are really geared towards that? Or are you seeing more companies that are looking for computer-industry, data-science type roles? Is that increasing, as well? >> I think companies are definitely looking for more data scientists and I think, also, people are figuring out that there are data science programs like graduate school programs and I think that supply of data scientists is definitely increasing, but at the same time, or more so, the demand for data scientists is increasing. And not to mention, the available data that's out there is increasing at a faster rate than anything else. Yeah, it is, I think, the best time to be a data scientist right now. >> Let me ask you one more question about looking at skills. We have such a great cross-section at this event of leaders in retail, in obviously, what you're doing in neuroscience-gaming-merging world. We've got professors here. Data science is such an interesting topic, it's obviously very horizontal. From a skill set perspective, kind of the traditional skills of being a statistician, mathematics, being a hacker, a lot of the things that we've been hearing around the show today, and really aligns with what you're doing is more on the behavioral insight side of, you have to be able to communicate what you're seeing and be able to apply it. I'd love to understand a profile of an ideal data scientist that you guys are seeing from your data. What are some of the other behavioral attributes that maybe are some of the non-teachable things that you're seeing that really come up that this would be a great career path for someone? >> Personally, I think intellectual curiosity is number one, and they would have to have strong self-motivation and discipline because you could love analyzing data and you could just be doing that for how many days, I don't know, and that's it. You could actually come up with a good story. You've got to be a good storyteller and if you have artistic flair to make the data beautiful, then even better. But it is important to go from the beginning of the project where you have a bunch of data set and actually come up with actionable results that people can use. And you're not only always going to be communicating with a data scientist, so you need to be able to present your data in a more succinct and easily-digestible way. >> That sounds like, as the chief data scientist for Pymetrics, that's what you're looking for to hire on your team. Give us a little bit, last question here, just a little bit of an overview of what your data science team looks like at Pymetrics, as you're helping to leverage this data to give people opportunities with careers. What does your team look like? >> Our team has a very diverse background. We have a few PhD's in Physics and you know, well, I have a PhD in Neuroscience and there's other data scientists with PhD's in Physics. We actually have one guy who majored in Data Science and we have another guy who majored in Bio Engineering. So it's definitely a diverse background. But the general theme is that you do need a good, quantitative foundation. So, whether it's engineering or physics, it is still helpful to have that statistical or analytical mind and if you can actually apply that, and actually love solving problems then I think data scientist is a right goal. >> So you're on the career panel at WiDS2017, is that the advice that you would give to kind of, the next generation of kids that are interested in this but aren't quite sure what industry they would want to go into? >> What industry? I think, I mean if they're even remotely interested in going into data science, I would encourage them to pursue it. I think it is one of the most fascinating fields right now and there's never going to be a shortage of needs for data scientists. So if you like it, if you think you are going to be pretty good at it, I say go for it. >> Fantastic. And you've got a great audience here. This is being live streamed in 20 cities, I think across the globe, or 75 cities, I have to get those stats right. But, there's a big opportunity here to be an influencer and we thank you for spending some time with us. Best of luck on the panel. >> Thank you. >> Thank you for watching. I'm Lisa Martin, we are live with theCUBE, at Women and Data Science 2017, #WiDS2017. Stick around, we'll be right back. (upbeat mellow music)

>> Live from San Diego, California It's the queue covering Sisqo live US 2019 Tio by Cisco and its ecosystem barters >> Hey, welcome back to the cubes. Coverage of Sisqo Live from San Diego. Sunny San Diego. I'm Lisa Martin with Stew Minutemen today and stew and I are very pleased to welcome to the Cube for the first time. Peter Sprigg gotta distinguished engineer from red Hat. Peter, Welcome. >> Thank you. I'm really excited to be here. >> We're excited to have you here today. I'd like to say Welcome to the sun. Its pretty toasty for in this very cool sales pavilion, which is Ah, very nice. A bright. So we got a lot of bright, but we do have some heat. So you've been with Cisco Cisco? No, actually. >> Was what? Siskel Ugo? >> Two degrees of Kevin Bacon Way where? In this room. Right. You've been with Red Hat since the answerable acquisition. One of the things that was funny that Chuck Robbins mention this morning was this the 30th anniversary of Cisco event with customers and partners. He also mentioned 30 years ago Seinfeld started. So I'm gonna do a Jerry Seinfeld on go digital transformation. What's the deal with that. >> You know, I think that, you know, one of the things that's really exciting and being part of Ansel and actually coming from the network's base. You know, we've had the opportunity to really be out in front of this whole digital transfer station. We've been doing it for you very long time on it's been just It's really been all about a journey on DH. That's really what I think. Earmarks. Really? What answer was all about >> Peter? So another thing. We've been on a journey a long time. That whole automation thing. Yes, we've been talking about that my entire career in the network. So bring us forward. You know, maybe, you know, did not 30 years. But you know what's going on in the last couple of years, That's different about automation, you know, 30 2019. Then we would have talked about, you know, when you first joined. And >> yeah, you know, I think that when I first joined, you know, everything was we were just trying to convince people that this is something you should think about doing you. Now you look around, you see what's going on here, alive and at definite and it's become a whole world unto itself. It's really starting to define its own space and networking, which is really exciting to see because I've been part of this journey really since the get go. And it's just it's really exciting to watch this homeworld start to come together. And people really taken interest in changing really the way that we approached, cooperating in >> person, and I'm glad actually mentioned the definite zone that we're in here. So there's lots of workshops happening right next to us. Hear developers really helping to drive that transformation software a big piece of your world. I'm assuming >> it is. It really is, you know, And I always love to tell the story of, you know, I've got a software development background, but I also have a network operations background watching these two worlds come together. It's so exciting and being out at the forefront, really pushing the envelope off. What we can do from an automation perspective is really been exciting >> so as to mention we're in the definite zone. This definite communities mass it is John Fourier and I had the opportunity to cover definite create back in Mountain View about six or eight weeks ago. I think that number this is Yoo, he mentioned, is 585,000 members, strong looking at Red hat and the spirit of this open source community. Talk to us about sort of the alignment of these communities and how this is helping to drive, not just technology forward, but be able to get that feedback from customers in any industry to drive these emerging technologies into mainstream. >> You know, I think you touched on the key there. It really is all about the customer and the customer's experience. You know, the wonderful thing about open source community is the fact that we can all come together. Vendor supply our customer, you know, consulting team, whoever you are, we all can come together, and it really does become right. We're all better together, and we're all pushing forward and trying. Teo really change the way that we approach how we build design and operate now destruction. >> Peter Peter Wonder if you've got a you know, a customer example. I know sometimes you need to anonymous things are what kind of things are customers Went, went when they're going through this. The outcomes and results that change how their business works, >> you know? So one of the things that and I got one particular customer mind. I can't say who they are, but one particular customer that that we worked a lot of time with him. What >> they were >> able to do is they were actually able. We gave them back the gift of time. That's what we talked about with automation. And what we mean by that is they were able to take a job that used to take them literally weeks to get done, that we could now automate and get it done once a night twice, you know, do it in a single night as opposed to them taking ways to get that job done. That frees them up to doing the more high value work. That networking here's really wanted you and not saddle them with more Monday and stuff. >> So just to follow up on that because, you know, traditionally that's been one of the pieces right is how do you know make my employees mohr efficient? Howto I give them more environment, something that they talked about. The keynote this morning is some of the scale and some of the you know you're dealing with EJ applications and all these environments is even if I had the resource, I probably couldn't keep up with the pace of change. Correct. They're doing so when you start throwing in things like a I and ML on top of those. But there's time to find their way intersect with what you're doing. >> Absolutely, they really are. And it's areas that we're starting to look into a swell. You know, Ansel's been doing this for a long time, but we're starting to see how do we bring some of these other two separate pieces and bring them together underneath this automation umbrella? And really again, we want to drive out that that everyday task out of of the operations Hansel. They can focus on the high value things of evaluating technology and moving things forward for their organizations. >> You say you were able to give that particular customer back the gift of time. I've got everybody breathing on the planet today, wants back the gift of time. But I would love to follow that story down the road because the gift of time has so much potential. Posit did impact all the way up to the C suite. Teo, you know, being able to move resources around to identify new revenue streams, new business nodules, new products, new services expanded into new markets. So that gift of time is transformative. >> Absolutely. Without, without a doubt, it is. And you know what we're seeing and what we're getting feedback from our customers on is that because of that gift of time, they're able to now focus on pushing their businesses forward. Right? And they're starting to solve challenges that have always been on that traditional, ever going task list. Right? That never you never get Teo. And they're really starting to be able to focus on those tasks such that they can start to become more innovative. They become more agile and they focus on their business, not on the active managing technology. >> All right, So, Peter, another another big theme of the show here is multi cloud, something we heard. A lot of red has something. Also, it's this skill set that one of the biggest challenges for customers working behind between those various environment. How sensible helping customers bridge some of those worlds today. >> Well, so you know, obviously, Ansel's not just a network to write. We automate anything and everything. And we like to talk about Ansel as the language of automation and really what it does for organizations. Whether you're looking at at infrastructure, whether you're looking at hybrid Cloud, what we do is we bring a language to the operations team where you get these two separate teams talking in a dialect that they can understand each other. And that's really what Ancel starts to bring your two. Those organizations. >> That internal collaboration. Absolutely. Maybe bridging business folks and folks who not wouldn't normally necessarily be driving towards the same types of solution. Correct? Correct. And it really >> kind of starts. And this is actually how we see Answer will kind of unfolding most organizations, right? It starts in these pockets, and small teams will start to use answerable. And then it just kind of grows and grows and grows. And what we find is all of a sudden, you've got, you know, a cloud Administrator's going out talk to a network engineer, and they can talk through this language of automation instead of trying to figure out how to communicate. They actually become productive immediately. >> OKay, Peter, Some of the big waves coming down the line that we're talking the keynote this morning, You know, five g y 56 You know, just incremental changes, you know, in your world. Or, you know, what will some of these new architectures that they're talking about, you know, have some dramatic impacts? >> Well, they're gonna have huge. In fact, you know, I think you know one of the things That's very interesting. You look at some of these technologies coming down, the coming down the ways now is everything is getting faster. I mean, that's nothing that we've been. You know, anyone who's been a knight for any period of time knows it's always faster, faster, faster. But what it's doing is is it's really motivating us to look at ants one and rethink how we do certain things so that we can keep up with the demand and allow organizations to, you know, meet the demands of their customers in accelerating their time to market. >> Maybe dig into that a little bit more in terms of the customer feedback. How are you guys? How is answerable being able to work with your customers across any industry, get their feedback to really accelerate what you guys are able to then deliver back to the market. What's that feedback loop? Well, I think >> you know, when you think about automation, automation is certainly it's a technology, but it's also very much about how organizations work, right? I like to talk about automation is really more a state of mind, Not so necessarily a state of action. And so therefore, you know, we spend a lot of time with our customers to understand how do they run their business and how Khun Automation become a way that they think about running the organization and really help them move forward. So we spent a lot of time understanding our customers business before we ever get into the bits and bytes of what automation really is. >> Yeah, you mentioned some of those organizational pieces, like the cloud guy in the network guy. What are some of the biggest challenges that you're seeing customers these days, and, you know, how are they helping to, you know, mature the organization to this new modern, multi cloud developer centric? You know, software defined, you know, Buzz, word of the day. >> You know, I think that you know, the biggest challenge that we see every single day with our car? Does Moses. You know, just where to get started, how you get started with. There's so much of it out there. Now it's it's they're looking at, and how do you get started with this? And how do you let this thing take on a life of its own? And so we spent a lot of time just getting them. You 123 steps down the road, get going in the open source and then let it expand from there. And we bring a whole suite of capabilities, then to the customer, whether it's through red at consulting, whether it's you're working through our open source communities to really help them on that journey. >> Wondering customer meetings. Where is this conversation now with respect to automation? Is he talked about giving the gift back of time. That would go all the way up to the C suite. So much potential there. Are you still having the conversation with more? The technical folks are where the lines of business or maybe even the executive sweet in terms of being a part of this decision in understanding the massive impact that automation will deliver. >> Yeah, it was just starting to see that that trend transition. Now, you know, we just came off of Redhead Summit, and we spent a lot of time talking with senior directors. See sweet individuals about kind of that transition in how automation is. As I mentioned before, it's no longer just a technical tool in the tool back. It really is becoming a business tool and how you could leverage it to really drive the business. So that's those conversations air starting now. We're just starting to see that, and it's really it's really exciting is really an exciting time to be part of this. >> All right, Peter, what will tell us a little bit about what red hats got going out of the show? I happen to show this to stop down the show floor, I saw the like command line video game, which I see that Red House seems that's making the go around there. I know your team's having a lot of fun team who can get the high score. What else at the show should people be looking at for red hat? >> Well, so you know, In addition, to answer. Well, of course, we also spent a lot of time talking about open shift, which is the other big red hat, you know, flagship product and really, what we're doing in terms of being able to deliver and the multi G hybrid cloud infrastructure and be able to run workloads in any cloud infrastructure, no matter where that may be. And then, of course, they'd always always comes back. Tio the operating system Red hat. Lennox, you know, they go hand in hand, way are always gonna be about the operating system, and everything kind of bubbles up from there. >> So here we are, halfway through calendar year 2019 which is scary. What are some of the things that you're looking forward to as the rest of the year progresses? Some, you know, exciting things going with Red had a big blue, for example. >> Well, there there is there. Certainly that although you could probably tell me more about how that's going that I get to know even anymore. But you know, I think really, What? What's exciting about the second half of this year and you're going to hear more about it? Actually, a definite this is a good time for me to mention this is that you know, we're doing a lot with Cisco right now. One of the things that course you know, Cisco's making a huge investment in definite and Red Hat is really becoming a very key partner with Cisco in that. So you're going to see a lot of open source community work around red Hand Cisco collaborating together to enhance what Ansel's doing and try and bring even more traditional and nontraditional people into these communities. >> More collaboration, I presume, over some of their cognitive collaborations, >> like absolutely, absolutely. >> That does work on linen because I've been using blue jeans most the time. >> It does. I You know, I I I pushed them really hard because yes, at first I had troubles with it, But yes, now it worked fantastic on Lenny. I couldn't be happier. >> You heard it. Here, Peter, Thank you so much for joining stew and me on the Cube this afternoon. We appreciate your time. I >> appreciate it. Thank you so much for >> having all right. It was fun for stupid aman. I am Lisa Martin. You're watching the Cube live from Cisco live in sunny San Diego. Thanks for watching