Alexis 0:00

Hello, hello, and welcome to the Smoko Podcast. My name is Alexis Armstrong, your host. Nice to meet you. The Smoko Podcast is the place to celebrate and highlight women, trans women, and non-binary folk working within stem and trade occupations. So please tune in, take a break, join us. We're on smoko today. We're extremely lucky to be joined by the lovely Elizabeth Jimenez. Ellie, who is a good friend and she works as a data manager at Series, which is the Cooperative Institute for Research in Environmental Sciences, and she's gonna talk to us today about her experience working at sir, her experience as a data manager, her background in geosciences, and specifically this. New discipline of geosciences, which is a mix between data, science, mathematics, and geology. And so we're gonna talk about that today. We're also gonna have a really important conversation and also talk about diversity and representation within stem. So thank you Ellie, so much for coming on the show today. It's

Elizabeth 0:56

good to see you too. And thank you for letting me join into your conversation. Oh

Alexis 0:59

my goodness. You're welcome. Anytime you would like to come on the show, Elliot, you freaking say the word Maybe just start us off, I ask everybody this one, but I'm always so genuinely curious is how did you discover this specialty? How did you discover geosciences and your specialty's a little bit different, that it's a combination of geology and mathematics and data science. How did you fall in love with this field? What was it about it?

Elizabeth 1:23

I discovered this, field in geosciences because I was first a geophysics major in my freshman year, and I considered the freshman year to be, a year of. Discovering what you like, what you don't like. I discovered I liked the field aspect that geology had much better. And the opportunity that you had of camping and being outside. And that's something that, just really resonated to me. Coming from a small town in Texas, that's something that I was looking for in my job. So that's what I went for. And honestly, I really enjoy having. Ability to go camping and be outside with my job.

Alexis 2:02

No, that's a perfect answer. That's how I got into it as well. Like I just found out that I could get paid to be outside and to live in the woods and go camping. And I was like, oh yeah, that's so easy. Like I'll become a geologist if that's what it takes to have that as my job. Sure. We've spoken a little bit about your specialty in geoscience and that data science is basically like the future of our industry, and I feel like you're steps ahead of everybody else that you're already in it. Could you describe what your field is and what that background is, and then what would be the role of data science in geoscience? How are those two linked?

Elizabeth 2:38

So my background is a mix of both geology and oceanography. I got curious about programming during my undergraduate classes, it wasn't even a class that it was required, but my degree. But I was just curious and I took it and I, I really fell for. Learning about environmental processes and how to understand it better using computers and computer programming. And that's honestly how I got into it.

Alexis 3:05

It's so cool that you took this. I love that you searched that out, that it wasn't a required course, but you took programming is it coding? Is it, cataloging the data? Is it creating the systems and architects to store the data? What does that actually look like?

Elizabeth 3:19

I do use Python and coding, to archive this data. And the pipeline was previously, Done and constructed by my boss and I'm working to keep up with it and, do, qa, qc with it. It's a teamwork. It's the process of, putting that together. But yeah, I'm happy. I pushed myself and I took that class randomly in college and that's how, what led me to where I'm now.

Alexis 3:45

I love that you were able to find this new fields, cuz that specialty and that combination of kind of computer science and like mathematics, truthfully. I love how you found your two passions of being like, I wanna go outside and go camping. Yeah. So I'm gonna take geology instead of geophysics. And then I love computers and programming and learning how to code, and then finding this kind of, This combination of the two. I think that's very special.

Elizabeth 4:09

So actually you're right about this all being new. That class was basically just a class that one of my professors put to the board and was like, maybe some of my students are interested. Yeah. And there wasn't any, program that was constructed yet. But the following years, it came together. And actually there's a lot of programs at Texting M that you can enroll in data science and all of that now. And honestly, it allows you to go into the workforce with all of those hugely valuable, assets and use them from day one in your job.

Alexis 4:48

I believe you guys are like the chosen ones in geology. I'm like, my goodness, you're ahead of us. It's such good skills. Because I think in geology, in some sciences, you're taught really old techniques, which are wonderful and don't get me wrong, but like I was taught on like paper maps and stuff. Yeah. And then like you go into the workforce and they're like, here's the 3D modeling program, please go model it. And you're like, oh, oh no. Like I was used to like a protector in like paper. Right? You have to all of a sudden learn really quickly on the job. And it's lovely that you have that, in education, you have that at the university.

Elizabeth 5:21

Don't get me wrong, you need those skills about learning them on paper. Yeah. Cause that really helps to understand what you're doing on the computer. Mentally thinking and 3D wise and learning how to use, a protractor and all of that, and making a map really helps you in being able to understand what you're doing with

Alexis 5:40

Coding wise. I'm not gonna put down, geology and paper maps. You definitely need it, but I do love that you guys also have that skill early on. And your role now, right? Like it gave you this beautiful foundation, you're working right now as a data manager at series. Could you explain what series is, what's the mission of it, and then what about this data sets and these data sets that you're working on? What makes them so important and may be different than other data sets?

Elizabeth 6:09

Yeah, so theories, as you previously said, is a co-op, it stands for the Cooperative Institute of Research and Environmental Science, and it's a cooperation between the University of Colorado in Boulder and Noah. And we're a group of 800 scientists that support Noah. We're a bit of a huge, big group. Which, does research in science and, to better understand your environment and the benefit of society.

Alexis 6:37

Oh my goodness. Yeah. No biggie. No biggie whatsoever. Benefit of society and understanding. I didn't realize how big it was. First off, I didn't realize it was 800 people. Do you guys collect the data as well, or does Noah collect it and then you guys process the data? Is that kind of how it works?

Elizabeth 6:54

We do both. We collect, and store the data. I specifically work on the side of storage in maintaining

Alexis 7:00

When you collect the data, is it similar data cuz Noah's all Ocean specific in paleo oceanography or oceanography? Is Sir Ocean also oceanography based or is it all environment?

Elizabeth 7:12

All environment. So my team is based in the ocean and that's what we study. I'm part of the archive of maintaining noise from whale and passive acoustics, but my coworker, she does sonar and other types of data that she archives.

Alexis 7:29

No wonder it's for the benefit of all society. It's if you guys are looking at basically all natural data sets.

Elizabeth 7:35

I have another coworker that works on tsunamis and creating a model that better interprets tsunamis, so that's very cool

Alexis 7:42

So it's a set of researchers and independent people that are looking at this data, working with Noah as well, collecting their own data. And then there's a collection side. And an archive side is a completely public

Elizabeth 7:55

For what I do, it's public and it's made for scientists and industries and governments to use. That's what we support.

Alexis 8:04

What a cool project and what a cool initiative to be a part of Ellie. The impact that you can have is pretty incredible and it's cool that it's all public, that everyone can see it. We've spoken a little bit, or you just mentioned it, that, your role is on the archive side and it's looking at whale specifically. Could you describe your roles and responsibilities maybe a little bit more, and then what does a typical day-to-day look like? My,

Elizabeth 8:28

role is a data manager and, they archive passive acoustic recordings from. And that might sound a bit complicated because the first time I delved into oceanography, I was like, what does that mean? I actually brought some audio samples, to better explain this and I shared it

Alexis 8:49

with you. Yes, you did. I listened to it all day and so we're gonna play it here

8:53

Want to share about to listen to is basically what Ellie gets to listen to. Almost every single day, this is her job, which is pretty incredible. So this would be an example. The data that she gets to hear. Here is the song of the whales.

Elizabeth 9:29

Heard were bailing whales and, those were actually recorded basically using. And an instrument that has a microphone and you put it underneath the surface of the ocean and you record those sounds and you can detect where those whales were and what species they were. And those recordings are day long, various hours, very huge. Data sets that are sent to me and I archive them and make them publicly accessible.

Alexis 9:59

The first time I heard that sound, I was just like, this is so beautiful and so striking and it's so cool that this is your job that you searched through these data sets and then try to find them. I have a couple questions on that. The first one, could you explain a little bit of how this data's actually collected? Because I know you said underneath the surface of the water, but is it mostly through marine expeditions or through boats, or is it like a buoy system? Where is this data coming from?

Elizabeth 10:24

Scientists actually have to go out on a ship and install these, microphones. Inside of instruments onto buoys, those buoys are left there for months, recording whales, fishes, fish, thrill, anything that it can. And then scientists take that back, which is raw audio. And, that is sent to me from then on. Scientists that collect that data actually are able to detect those species and that is also sent to me and I archived that.

Alexis 10:58

I feel like you probably learned about it in oceanography and school as well and that's really cool to be part of that cuz those buoys are some of my favorite things in the entire world. The fact that we have buoy systems all over the world, just collecting data every single day. I think it's fascinating. So that's cool that you get to see that raw audio. The second question of that is with the whale species identification, so is that sent to you already completed by the scientist or do you now have an ear that you can listen to a certain type of bailen whale and you're like, yep, that's a hump back. That's a sperm whale.

Elizabeth 11:30

I actually receive the data once it's already. Been detected. And then make that available. It's a, resource for scientists all over to better understand where they're located and maybe whatever project they're working on, maybe they need samples of whales, of earth specific ship or something because you can also, get background noise From ships and all of that actually. You can use that for any research project you wanna do, or, a little side project.

Alexis 12:00

Do you have a favorite species, like when someone sends in like a humpback that you're like, ah, yeah, this is my favorite one.

Elizabeth 12:08

Not currently, but I should,

Alexis 12:12

I'm sure you will eventually get one that you're like, ah, not this whale again. Like, I hate these guys. Or like, there's something about that song of the whale that's not for you. I feel like you could take a lot from it. You could take my population size, you could take migration, you could take, behavior. I'm sure you can probably tell if some are juveniles or babies or moms and that's really cool. It's a cool thing to do all day. Maybe you love this because of the whales, but what's something that you love about your job? What's something that's a little bit challenging?

Elizabeth 12:42

Something that I love is continually learning. Data science and encoding. There's always something you can improve on and something you're learning about. Improving on my coding skills on the job is something that I really love. And then, something challenging is when I get a lot of drives from, data providers and I have a lot of, data on my desk and I have to go through it. It's a bit challenging.

Alexis 13:08

I could imagine just like the amount of data that you guys receive, because I think you guys are a unique organization I love the answer of continuously learning one. I could imagine that with coding and with data science, because it's such a rapidly changing specialty and it changes with new technology, is there something that you're learning right now specifically that you're super juice step on, or want to learn on?

Elizabeth 13:32

A skill that I'm recently working on is learning how to use Python and working with a database. Because I didn't have a database I could work on or access or do projects during college. I didn't have that skillset. So it's something I'm learning on the job and I'm really enjoying to learn. And then something in the future that I'm gonna have to learn is we're migrating into the cloud, okay? So all of our processes are gonna be, cloud-based and interacting in the cloud. So those are new skillsets that I'm gonna have to, learn, and I'm looking forward to that.

Alexis 14:05

How is it different from working right now? Python versus cloud or Python? Like at school, were you just learning the basics of Python but didn't have the database to actually apply it and then now all of a sudden it's far bigger? Is Python and cloud totally separate things?

Elizabeth 14:20

You can interact with the cloud using Python. Used the cloud and interacted with it, but we're gonna be in a much more in depth process later

Alexis 14:32

in the future. It'll go from like knowing maybe a little bit about it, using it once in a while to all of a sudden to be like, your entire life is cloud-based. Right. And you need to understand and organize this program and create the structure of it probably. As well. Correct. Okay. Oh, that's gonna be exciting.

Elizabeth 14:50

Definitely a challenge.

Alexis 14:52

Is there anything that has really stuck out in it that has been unexpected that you've discovered in the data? Is there anything that you've discovered that you're like, oh my goodness, this is crazy.

Elizabeth 15:03

So something that has been unexpected is the customer base. So apart from receiving the data, we also provide the data to the public. Nothing contacted by a lot of, high school students asking for data for projects. That's something I did not expect. No. For high school students to ask for data and honestly, it's very impressive.

Alexis 15:27

That cracks me up about it is, they're basically just cold calling the US government. Hey, I found your email. Like you're this national organization. It's not like it's a local small time thing. It's a huge organization and for a 16 year old kid to be like, yeah, I'm gonna cold call the US government and I'm gonna get your data is hilarious, is amazing. And kudos to them. I love that confidence.

Elizabeth 15:54

So we actually have our websites that are publicly available and they're hosted by Noah. And you can access and request that data.

Alexis 16:03

Still, it still takes that next level kind of 16 year old confidence, but I love that energy. That's what we need in science. Any, unexpected like sounds or unexpected things captured by this kind of raw audio, or has it been mostly surprised by who's been asking for your request?

Elizabeth 16:21

What has been, the surprise of who's been asking. We do get a lot of whales and, real sound, but yeah, it's for me because I interact with the public and make sure that they get the data that they want, that has been something very surprising to me. The other question that you asked, if we work with any other government entity, so we do have a connection to the US Navy. They make sure that all of the data that we make publicly available, it has been, given security clearance just to make sure that we aren't putting, anything that could be bad for security and national security. The Navy is in charge of, clearing all of that before we receive that data.

Alexis 17:03

Wow. That's something that I wouldn't expect either, right? I was just being so like narrow and science focused that you're like, you wouldn't even think to be like, yes. You're probably also could take up acoustics from submarines or from ships. Yes. Or, and like from that you can look at migration of ships instead of just looking at migration of whales. So I didn't even consider that, that's a crazy aspect of the data. That's a wild thing that even has to be. Part of your process, have you ever been contacted by the US Navy? If anything has skipped or they've talked to you or does it happen before you get the data?

Elizabeth 17:39

It happens before it gets. To me. So yeah, the data providers sent their data to the Navy and then the Navy sends it to us. So none of the data that we receive

Alexis 17:50

has that possibility. It's already been pre-cleared and pre-scripted. It's a weird connection that I wouldn't immediately think, but it's correct. You can't put all of that type of sensitive data on a public database for the world to see if it hasn't been, properly scrubbed and probably looked at. When we're talking about your job and talking about geoscience and talking about data science and geoscience, where do you think the future of this industry is gonna go? What's something that excites you about this field? What era do you think this future of this industry is gonna go?

Elizabeth 18:22

I think, Geoscientists moving towards a better understanding of global processes through machine learning and ai. That's the way I think it's gonna grow. And we're seeing it in new projects that if you go to conferences you can see that already happening, but in a much more in depth is where I think, we're moving towards.

Alexis 18:44

Could you explain those? I haven't been in the conference circuit for a little bit, so I'm ignorant to it. What is an example of that project using deep learning and machine learning in geologic processes? What does that look like?

Elizabeth 18:58

Machine learning is basically teaching a computer. The same process how a child learns. Okay. The way I think about it is, when you're a child and you're playing with, those little triangles that are made out of wood And you try to get the red cube into the red little square. Basically you're teaching the child how to match colors. The child struggles in the first times, and then after a couple of times it learns that process and it learns that red goes with red. And that's the same kind of logic that is going on with machine learning and ai. One of the projects that I was potentially thinking about doing, is I saw, an issue during my college so one thing that really takes a lot of time is, identification of minerals. It's hard and you have to have an eye for it. But if you were to show a computer various images and have the identification already done, it would essentially learn. What a mineral looks like under the microscope, which is something you could use machine learning and teach and speed everything.

Alexis 20:04

Oh my goodness.

Elizabeth 20:06

That's a project I've wanted to work on. But yeah, it's been on the sideline a little.

Alexis 20:11

Yeah, that is an amazing project. Do you know how much time that would save you during like thin section analysis? Looking at slides that is the bane of your existence. I'm trying to do like your little heat maps? Ugh. Is it a true 30% or is it 25? Like it takes forever to do that.

Elizabeth 20:27

Right. And that's what machine learning can do in geosciences. And there's so many different aspects and different avenues you could take this into. So that's where I think. Geoscience is moving towards making discovery and better understanding of our environment, much more efficient.

Alexis 20:47

Thank you for explaining it so simply because I don't really know what machine learning is. I've learned about it, but I don't actually understand the concept of what it actually means on the program side of how do you create machine learning within a computer system or within a computer program. But geoscience, it's such, an interpretive science. If you're trying to establish patterns and recognition of colors, of faults, of minerals, it would be really nice if you could have that database and if you could automate The main thing with geology is like 10 geologists will look at the same rock and they'll say it's 13 different types of rocks. It would be really nice to have a little bit of help there and a little, programming power behind it. When do you think that future's gonna be? Do you think that future's already here or do you think it's in the next like 10 years?

Elizabeth 21:33

We're at the beginning of it. I think we're exploring, that's the beauty of science. It's all about experimenting and see where things go and what it leads us to. I think we're at exploration in that sector is where I think we're.

Alexis 21:49

The exploration side of it. Being on the data side of it, do you have any concerns about that? Because I know that's something that a lot of people talk about is AI and the dangers of ai. Should we be concerned in geoscience or do you think it's just a positive on pattern recognition?

Elizabeth 22:05

With programming, you have to make sure that. There is some caveats and something you have to pay attention to is don't get too comfortable As we said previously, you have to know what your map looks like on paper so that you understand it. The same thing with machine learning and other technologies. You have to understand what's going on to be able to notice if there were errors that were skipped on. If your result was good, what is your result telling you? Can you really are those questions are something that we shouldn't get comfortable with and we should always be questioning.

Alexis 22:44

The foundations of science basically, and the foundations of quality checking in your data to be like, can we trust this data set? Can we trust that measurement? How was it created? And then the implications of that data, what does that actually mean in the system? I love it. Thank you very much Ellie, for walking through your specialty and your job A switch completely I know that something that's really important to you is representation and increasing diversity in stem and. One story that always stays in my mind forever. For the rest, the all of time, is when me and you, we were on the ship and we were talking about jury duty and how every single person hates jury duty. And they were all complaining and bitching that they were part of it. And you were so excited and you're like, it's my duty to go to jury duty because I live in a community that's predominantly white. I'm. A Latina in my community, I'm a rarity with an I. My voice and my opinion needs to be heard. And so I wanna represent my community and I wanna go to jury duty. And it was a complete different viewpoint that no one else had shared or even had thought about when they were in that same position, when they were being selected for jury duty. For me, it changed my mindset of it and it reframed it. And I will always think of that moment. I absolutely love that story. It lives in my head, rent free. And I know, diversity representation is really important for you. Could you maybe describe the role of representation in your career, why it's so important to you, and then your experience being a mentor for young women and Latinas in geoscience.

Elizabeth 24:14

So first off, thank you for bringing back that You're welcome. The story about the

Alexis 24:18

jury duty.

Elizabeth 24:20

I think about that too. Representation is very important to me basically because I've felt, and I am a minority in STEM since I was in, placed in advanced classes in middle school all the way to my current job. it feels different. I felt different since I was in middle school, but you get used to it at some point, and then randomly you start feeling uncomfortable again? I think it's specifically very important, by diverse workforce because it allows us to talk, with people from different backgrounds and different views of how they see it? How they see issues. so that's something that is very important to me and, it's a change that I do see happening in, my industry. Specifically with younger generations. Like my generations and, new employees that are being, hired. But I do see the difference between my generation and older generations. That change is happening and it's something that we have to continue, putting effort into.

Alexis 25:23

I'm happy that the change is happening. You can already see it. When you look at like older generation to the new generation, even like to my generation or yours, that the change is already starting and beginning. I do think that we need to keep on having these conversations and. It has to be top of mind, for everybody within the industry and within the culture of it to make an actual meaningful change. And to be like, I'm used to feeling uncomfortable. I couldn't imagine that. And then all of a sudden it does come crashing back to you for sure. Of course it does. To be like, Nope, I'm still different. it still feels really uncomfortable. Being a girl in geoscience is already something that feels like a target on your back sometimes or You feel different than your colleagues. I couldn't imagine another layer to it and just, I'm sorry that you had to deal with that.

Elizabeth 26:08

If that's what you hung up, you have to work

Alexis 26:10

with it. In your career, has there been. Something actionable that has made you feel welcome or not tokenized. What's something that the community can do to support you and to increase diversity in stem, to make that environment more welcoming?

Elizabeth 26:25

So something that has helped me. To feel included and tokenized, definitely to be included in decision making conversations and having people actually listen is the key part into what you have to say and what your opinion is. That has made me feel very well.

Alexis 26:43

Being included within decision making and then listened. Is that kind of the actionable step? Is there anything else that helps, or is that the main one?

Elizabeth 26:53

I think that's the main one for me.

Alexis 26:56

Being a mentor and representation yourself, right? To be a mentor yourself, what's your advice to other women and to other Latinas just starting within this community and within this industry?

Elizabeth 27:08

Whether it's this industry or any other, I would say to believe in yourself, and if you have grit and you keep at it, it'll all work out.

Alexis 27:21

It's simple, but it's perfect. It's just grit. Believe in yourself. Keep going. Yeah. I love that advice for it. In terms of diversity, in terms of representation, is there anything right now within the industry that gives you hope? Is there initiatives or organizations that you really, can see yourself in and, resonate with?

Elizabeth 27:44

Internally in where I work, there are groups of minorities and having those conversations and you can listen in and it's like an open office meeting where anybody can speak up and, conversations are being had, which is something surprising. And I was very delighted to see, when I joined, my workplace. That's something that I really enjoy. You, ask me how can the industry or workplaces better support, minorities in stem? So I think the key part of this, is that the change needs to happen and we need to make it happen. For now and coming into the future. How I got here is actually I was introduced to STEM through a field trip, to the Shell Company in Houston, into their office. So they actually invited all of the seventh grade girls. From my school. We were invited to go talk to women engineers and we did a hands-on project where we built a floating device out of, anything we could find at home. Learning from women engineers what STEM was and the importance of it at a young, very young age Is what open eyes to all of those possibilities. I didn't even know what an engineer was at that age. What it really meant for a woman to be in science. So that definitely opened my view into other resources and that's something that I think companies should really invest on. Having that outreach to a younger audience

Alexis 29:28

Thank you very much for telling me that story. That's fantastic and I think it's great advice for an organization, cuz you're right, they have the ability and they have the funds to really invest in early education and in STEM and in engineering I love that you had no idea what an engineer was until you had this kind of like interactive moment. What's beautiful about that is that when you're older and you hear about engineering and when you're talking about oh, hey, what are you gonna do in the future? You now have this blueprint. You have this viewpoint that an engineer can be a woman because you saw it when you were seven years old. That foundation has already been built of representation early on to be like, yep. I look like an engineer. I look like a scientist. It's not someone who doesn't look like me. You also mentioned at work that you have, groups and minority groups that are talking together and talking about what does diversity look like in our workplace and within our organization. But like you said, something that's helped you feel included or feel non tokenized within this industry is when you're giving decision making power. And I'm guessing that organization also has decision making power within your organization.

Elizabeth 30:40

Yes, they do. They do talk to, decision making like the higher ups, people on board. Basically making sure that every voice is heard is, the mission of that group.

Alexis 30:54

And that's fantastic that you have a direct way to speak to higher ups and to speak to decision makers within the organization and to make an impact. Thank you so much for talking about everything today. I really appreciate it.

Elizabeth 31:05

Thank you for allow me Thank you for letting me join into the conversation and anytime you want me, to join in, just let me know.

Alexis 31:14

Okay. I will keep you to it. Thank you so much for talking with us today. It's so lovely to see you. Thank you for coming on the show. Okay, bye guys. Thank you for listening. This is the Smoko Podcast.