(upbeat music) >> Hey, everyone. Welcome to theCUBE's coverage of Women in Tech: International Women's Day, 2022. I'm your host, Lisa Martin. Erin Chu joins me next. Life Sciences Lead at AWS Open Data. Erin, welcome to the program. >> Thanks so much for having me, Lisa. Tell me a little bit about you and your role at AWS. >> I would love to. So I am a life sciences lead on the AWS Open Data team, and we are really in the business of democratizing access to data. We believe that if you make high quality, high impact data openly available in the cloud, that people can start innovate, make discoveries and do science faster with those data. So we have a number of specialists with expertise in different domains. Geospatial sciences, climate sustainability, statistical regulatory and then of course myself, the life sciences lead. >> So, you have a really interesting background. You're a veterinarian by training. You have a PhD, you've worked in mobile veterinary clinics, and also in an animal genomic startup, how did you make the change from the clinical side to working for a large international, one of the biggest companies in the world? >> Yeah, I love that question because so much of, I think, anybody's career path is serendipitous and circumstantial, right? But the fact is I was working in a mobile veterinary clinics while I was finishing up a PhD in molecular genomics. And at the same time was reached out to by a professor at Cornell who had started a little dog genomic startup. And he said, "Hey, we need a veterinarian who can talk to people and who understands the genomic side of things?" And I said, "Yeah, I'm your girl." And I came on full time with that startup towards the end of my PhD, signed on after I finished, came on on as their senior veterinary geneticist. Startups a great whirlwind. You end up learning a ton. You have a huge, deep learning curve. You're wearing every possible hat you can. And after a couple years there, I wondered what else I could do. And simply said, where else could I look for work? And how else could I grow? And I decided to try the larger tech world, because I said, this is a toolkit I don't have yet. So I'd like to try and see how I can do it, and here I am. >> And you, I was reading about you that you felt empowered by the notion that I have to trust my instincts. You look at careers in biology, you decided what directions you wanted to take but how did you kind of conjure that feeling of empowerment? >> Yeah, I have to see say I have an incredibly supportive team and in supportive manager, but a lot of it was simply because I've never been afraid to fail. The worst thing that someone can ever say to you is, no or that you didn't do that well. Once you come across that once in your life, it doesn't hurt so bad the second time around. And so, I was hired for a very specific data set that my team was helping to manage. And that does take up a good deal of my time, it still does, but I also had the freedom to say, "Hey, what are the trends in biology? I am an expert in this field. What do I know is coming around the corner? What do I know my researchers need?" And I was entrusted with that, this ability to say, "Hey, these are the decisions I think we should make." And I got to see those outcomes fairly quickly. So, my managers have always put a good deal of trust in me and I don't think I've let them down. >> I'm sure you haven't. Tell me a little bit about some of your mentors or sponsors that have helped guide you along the way and really kind of feel that empowerment that you already had. >> Absolutely. Well, the first and foremost mentor in has been my mother. So, in the spirit of International Women's Day, my mom is actually the first Asian engineer to ever reach executive level. Asian female engineer to ever reach executive level at IBM. And so, I spent my life seeing what my mother could do, and watching her just succeed. And I think very early it clear, she said, "What can't you do?" And that was kind of how I approached my entire life, is what can't I do, and what's the worst thing that will happen. You fail and then you try again. So she is absolutely my first mentor, and a role model to me and hopefully to women everywhere, honestly. I've had some amazing teachers and mentors. My professor who oversaw my PhD, Dr. Paul Soloway. He's currently still at Cornell, really just said, "What decisions do you want to make?" And, "I will support you in the best way I can." And we learned a lot together. I have a professor at Cornell who I still come back. I speak at her alternate careers in veterinary medicine because she just... And she was the one who told me, "Erin, you have a really high buoyancy factor. Don't lose that." And her name is Dr. Carolyn McDaniel. And she has just been such a positive force just saying, "What else could we do?" >> Well, that's- >> And, "Never let your degrees or your training say that this is what you have to do. Think of it as a starting point." >> That's a great point. We often, especially when we're little kids, many of us, you think of these very defined, doctor, lawyer, accountants, nurse instead of having something like you do and being able to go, what else can I do with this? How can I take this education, this information and the interest that I have and parlay it into something that really can kick the door wide open. And to your point, I love how your mom was saying, "What can't you do?" That's a message that everyone needs to hear. And there's an AWS Open Data Sponsorship Program. Talk to me a little bit about that. I'm always interested in sponsorship programs. >> Oh, thanks for asking. So the Open Data Sponsorship Program or the ODP since Open Data Sponsorship Program can be a little mouthful after you say it a few times, but the ODP is a program that AWS sponsors where we will actually cover at the cost of storage transfer and egress of high impact data sets in the cloud. Basically, we know that sometimes the barrier to getting into cloud can be very high for certain providers of gold standard data sets. And when I mean gold standard data sets, I mean like NASA Sentinel-2, or the National Institutes of Health Sequence Read Archive. These are invaluable data sets that are ingested by thousands if not millions of users every day. And what we want to do is lower that barrier to cloud and efficient distribution of those data to zero. So, the program is actually open to anybody. It can be a government entity, it can be a startup, it can be nonprofit. We want to understand more about your data and help you distribute it well in the cloud. >> So this is for any type of organization regardless of industry? >> That's right. >> So, you're really allowing more organizations... One of the things that we say often when we're talking on theCUBE is that every company these days is a data company, or it has to be. Every company has to be a tech company, whether we're talking about your grocery store or AWS, for example. So helping organizations to be able to take that data, understand it, and have those personal conversations that as consumers we expect is critical, but it's challenging for organizations that say, "Well, I came up in retail and now I've got to be a tech company." Talk to me about kind of empowering organizations to be able to use that data, to grow the organization, grow the business, but also to delight customers 'cause of course we are quite picky. >> You're so right. Data is power and it doesn't matter what you are selling or who you are serving. If you have the data about your product. And also to some degree, the data about who your consumers are, you can really tailor an experience. I always tell my colleagues that data is impersonal, right? You can look at bits and bites, numbers, structured columns and rows, but you can funnel data into a truly personal experience as long as you do you it right. And hopefully, when I work with my data providers I ask them, how do you want people to use your data? What are the caveats? How can we make these data easy to work with? But also easy to draw correct insights from. >> Right, that easy to use is critical because as you know the proliferation of data just continues and it will continue. If we think of experiences. I want to go back to your experience. What's been the biggest learning curve that you've had so far? >> Oh my gosh. So, the best part of being at a large company is that you're not in the same room or even like whatever the same slack channel as all of your colleagues, right? Coming from a startup or clinical space where quite literally you are in the same room as everybody 'cause there are less than 60 of you, you could just talk to the person who might be an internal stakeholder. You had that personal relationship, and frankly, like most of the time your views were very aligned. It was sell the product, get to MVP. Moving into larger tech, the steepest curve I had other than becoming very comfortable in the cloud, in all the services that AWS has to offer, were to manage those internal relationships. You have to understand who the stakeholders are. There typically many, many of them for any given project or a company that we're serving. And you have to make sure that you're all aligned internally, make sure that everyone gets what they need and that we reach that end to ultimately serve the customer together. >> Yeah, that communication and collaboration is key. And that's something that we've seen over the last two years, is how dependent we've all become on collaboration tools. But it is a different type of relationship. You're right. Going from a clinic where you're all in the same room or the same location to everyone being distributed globally. Relationship management there is key. It's one of my favorite things about being in tech is that, I think it's such a great community. It's a small community, and I think there's so there's so much opportunity there. If you're a good person, you manage those relationships and you learn how to work with different types of people. You'll always be successful. Talk to me about what you would say, if someone's saying, "Erin, I need some advice. I want to change industries or I want to take this background that I have, and use it in a different industry." What are the three pieces of advice that you would share? >> Oh, absolutely. So, the first thing that I always talk with my... I have quite a few colleagues who have approached me from all different parts of my life. And they've said, "Erin, how did you make the change? And how can I make a change?" And the first thing I say is let's look at your resume and define what your translational skills are. That is so big, right? It doesn't matter what you think you're a specialist in, it's how generalizable are those specialty skills and how can you show that to somebody who's looking at your resume. Let's call it a nontraditional resume. And the second is don't hesitate to ask question. Go for the informational interview. People want to tell you about how they've gotten to where they are and how you might be able to get there too. And so I say, get on LinkedIn and start asking questions. If one person says yes, and you get no responses I call that a success. Don't be afraid of not getting a response, that's okay. And the last thing, and I think this is the most important thing is to hold onto the things that make you happy no matter where you are in your life. It's important to realize you are more than your job. It is important to remember what makes you happy and try to hang on those. I am a gym rat. I admit that I am a gym rat. I'm in the gym five days a week. I have a horse. I go out to see him at least two or three a days. I know it's typical veterinarian, right? You just collect niches until you run out of things you want to pay for. But those are things that have been constant through 20 plus years of being in the workforce. And they've been what kept me going. Let's revise that in ten years. >> So critical because as we all know tech can be all consuming. It will take everything if you let it. So being able to have... We always talk about the balance. Well, the balance is hard. It's definitely a way to scale, right? It's going back and forth, but being able to hold onto the things that actually make you who you are, I think make you better at your job, probably more productive and happier. >> I agree. I totally agree. >> Another thing that you believe, which I love, this is an important message is that, if you look at a job, I like how you said earlier, the worst they can say is no. You have nothing to lose. And it's really true. As scary as that is same thing with raising your hand as you say, and I agree with you about that. Ask a question. It's not a dumb question. I guarantee you. If you're in a room or you're on a Zoom or even in a slack channel. A fair number of people probably have the same question. Be the one to raise your hand and say, "Maybe I missed this. Can you clarify this?" But you also think that you don't have to meet all the job requirements. If you see something that says, five years experience in this or 10 years in that or must have this degree or that degree, you're saying you don't have to meet all that criteria. >> I agree. Yeah, that's another big thing is that, I'll literally talk to people who are like, "Well, Erin, this job application, look at all these requirements and I can't fill these requirements." I'm like, "First of all, who says you can't?" Just because you don't have a certification, what has your work thus far done to reflect that? Yeah, you can meet that requirement, even if you don't have an official certification. But two, like what's the worst thing that happens. You don't get a call back from a recruiter. That's okay. I have so many friends who are afraid of failure, and I tell them, just fail once doesn't hurt. It never hurts as much as you think it's going to hurt. And then you just keep going. >> You keep going and you learn. But you've also brought up a great point about those transfer growth skills or those soft skills that are so important. Communication skills, for example. Relationship building skills that may not be in that written job description. So you may not think about actually there's a tremendous amount of importance that these skills have. That having this kind of breadth of background. I think is always so interesting we think about thought diversity, and if we're talking about women in tech. We know that the number of women in technical roles is is still pretty low, but there's so much data that shows that companies that have even 30% females on their executive staff are more performant and more profitable. So that thought diversity is important, but we need more women to be able to feel that empowerment I think that you feel. >> Yes. >> So when you think of International Women's Day with the theme of breaking the bias, what does that mean to you and where do you feel we are in terms of breaking the bias? >> Yeah, so it's interesting, I was just on a working group with some of my colleagues from our larger organization at AWS. And we were talking about, what are different kinds of bias and what our strategies to go ahead and combat them. The fact is we are all making progress and it has to be in one step at a time. I don't think that if we snapped our fingers, things would just go away. You have to take one step at a time. I also come at it from a data perspective, right? I'm a data person. I work with data. And like I said, data is, or data are, if you want to be correct. Data are impersonal, right? They are just statistics, their numbers, but you can use data to suddenly say, "Hey, where are the biases? And how can we fix them?" So I'm going to give you a great example. So my mother, again, a wonderful woman, a super amazing role model to me. She was diagnosed with breast cancer last year. And she being a smart lady, actually looked online. She went online on Google Scholar and PubMed Central. And she said, "May, look..." May is my little nickname. She goes, "Look at these numbers." She said, "My prognosis is terrible. Look at these numbers, how can you say that this is worth it. That chemotherapy is worth it." And I looked at it and I said, "Mom, I hate to break this to you. But this is a retrospective study of several thousand women from the Bavarian cancer registry." And you might guess I am not a Bavarian origin. I had a chat with her and I said, "Mom, let's look at the data. What are the data? And how can you take away stuff from this with the caveat that you may very well not have the same genetic background as some of the women or most of the women in this registry." There are biases. We know when we look at population sequencing, when we look at the people who are sequenced, the people who put in medical survey information. There are not representations of certain ethnicities of certain sexes, of certain parts of the country. One of the things I really want to do in the next three years is say, how can we support people who are trying to increase representation and research so that every single woman gets the right care and can feel like they are themselves represented in what we call precision medicine or personalized care. >> Absolutely. >> That's a long story. >> It was a great story. >> That was a long answer to answer your question. >> You talked about how your mom was a great inspiration to you and it sounds like you've been quite a great inspiration to her as well. Was a delight talking with you, Erin. Congratulations on your success on being able to be one of those people that is helping to break the bias. We appreciate your time. >> Thanks, Lisa. >> My pleasure. For Erin Chu, I'm Lisa Martin. You're watching Women in Tech: International Women's Day, 2022. (upbeat music)