S3E14: Rachel Wagner-Kaiser—The Pivot That Changed Everything

Ever feel like the path you’ve worked so hard for… just isn’t yours anymore?

In this episode of Unmute Yourself, I sit down with Rachel Wagner-Kaiser—a data science and AI consultant, author, and former astronomer—to talk about the courage it takes to pivot when everything you’ve built feels like it’s on the line.

Rachel’s story is incredible: from earning a PhD in astronomy to stepping into AI and data science before it became “hot,” she shows us that growth often lives in the space of doubt, discomfort, and uncertainty. This isn’t a perfect story—it’s real, messy, and inspiring.

When we sit down, Rachel shares:

•  How to navigate a career pivot when you’ve invested years in one path 
•  Why fear, failure, and self-doubt aren’t just obstacles—they’re fuel for growth 
•  How to trust yourself even when the next step is unclear 
•  The truth about AI and machine learning beyond the hype 
•  The mindset shifts that help you embrace change and step into your own power 

If you’re feeling stuck, questioning your next move, or wondering if you’re capable of something new, this episode is for you. It’s a reminder that the life you’re meant to live might be just on the other side of fear—and the first step is saying yes to yourself.

If you’re carrying a decision you already know you need to make…
You’re welcome to book a private coaching call with me:
https://calendly.com/jennifer-flashlightthinking/strategy-call

Stay connected and don’t miss an episode:
https://linktr.ee/unmuteyourselfpodcast

Connect with our guest: Rachel Wagner-Kaiser
Email: rachelwk82@gmail.com
LinkedIn: https://www.linkedin.com/in/rawagnerkaiser/

Connect with me, Jennifer
LinkedIn: https://www.linkedin.com/in/jennifercartersocialimpact/
Instagram: @unmuteyourself
Website: https://flashlightthinking.com

 Where in your life are you being called to pivot—but still hesitating?

 00:00 – Welcome & Rachel’s journey
 02:00 – Early love for science
 04:30 – From astronomy PhD to pivot
 07:00 – Fear, doubt, and career change
 12:00 – What data science really looks like
 16:00 – AI: hype vs reality
 21:00 – Critical thinking in today’s world
 25:00 – Confidence and growth
 30:00 – Writing a book
 34:00 – Stepping outside comfort zones
 38:00 – Lightning round
 45:00 – Final reflections

 Music: “Your Way” by Mark July
 Licensed by Uppbeat
 License code: KKHUU4BLYO3R5SKJ
 https://uppbeat.io/t/mark-july/your-way

 #UnmuteYourself #CareerPivot #WomenInTech #PersonalGrowth #SelfTrust #AI #DataScience #MindsetShift #Leadership #GrowthJourney

Transcript

SPEAKER_00 0:15

Okay, welcome back to Unmute Yourself, and I'm your host, Jennifer Carter, and this podcast is about lifting the curtain on leadership, purpose, and the real stories behind women who dared to do things differently. And we'll talk about how they found their path, the struggles along the way, and how they built something that truly matters. And these are normal people doing extraordinary things because I want you to know you are extraordinary too. Today's guest, I have to say, I'm super excited because she, like me, is a native Michigander. And her name is Rachel Wagner Kaiser. She is a data science and AI consultant based in Seattle. She grew up in Battle Creek, Michigan. Woo, Michigan, and studied physics and astronomy, right? Mind-blown already. And eventually pivoted into data science long before it became the hot career path it is today. And now she works with companies to build machine learning and AI solutions that automate complex processes and help teams make better decisions. Her work sits right at the intersection of science, technology, and real-world problem solving. Rachel, welcome to the show. Thank you so much, Jennifer. I'm excited to be here. Okay, so let's start at the beginning. So you grew up in Michigan, which is a pretty different environment than where you live now in Seattle. So, like, how did you get drawn to science and math when you were growing up?

SPEAKER_01 1:47

Yeah, it's a great question. My parents were always, they weren't in the sciences. My dad was a social worker and my mom was a psychologist, but they both really loved science. So we were always going to museums and aquariums, and like Chicago has the best science museum ever. So whenever we were in Chicago, we would always go there. And I grew up with science being a part of my life. So it was always like a side interest. And when I was in high school, I happened to go to a talk by an astronomer who was talking about the topology of space. And it just blew my mind. It was like I've never thought about that before. I couldn't wrap my brain around it. And it was the first time I felt like I my brain just hit a brick wall where I like couldn't comprehend something no matter how much I thought about it. And that just like drew me right in. I was like, I love this field of astronomy. It's amazing. Let's do more of that. And that's really what put me on the path of astronomy in particular through college and grad school. Just fell in love with it.

SPEAKER_00 2:49

So, like, okay, so what does one do with an astronomy masters? Masters, right? Yeah. You have a PhD.

unknown 2:58

Of course.

SPEAKER_00 2:58

Yeah. Oh, just have a PhD in astronomy. You have a PhD in astronomy.

SPEAKER_01 3:03

Yes, yeah, exactly. But it's a valid question. It's like, what do you do with that? And uh when I was in grad school, I realized like pretty much the main track for most astronomers is being a professor, which allows you to do more research, which is great. I loved the research, but I also didn't really want to be a professor. Yeah. And that's that really is the main career track for astronomers. There, there are a few like research-only positions here and there, but like people always ask, like, well, why don't you go work at NASA? And it's like, NASA is mostly engineers. They only need so many astronomers. Right. So, really, like being a professor is like the main career path. And when I was in grad school, I realized like that wasn't as exciting to me, even though I really liked the research and like working with data and looking at the stars. Well, what was your dissertation? My dissertation was on very old clusters of stars, like 10 billion years old and older, that are in our galaxy in the Milky Way and in nearby galaxies. And there is this mystery, which I think is still ongoing, where in these clusters of stars, you have two different populations that are chemically different. But the way that these star clusters form, like that shouldn't be the case at all. All the stars should be chemically very similar. So the work that I was doing was looking into this and trying to understand more about the properties of these clusters and the stars within the clusters to try to figure out like why might that have happened. Right. Of course, I didn't get to an answer. You know, science moves slowly, so that's okay. Right. But it was really cool. I I loved it. Yeah.

SPEAKER_00 4:35

That's so cool. Do you miss it?

SPEAKER_01 4:36

I do sometimes. Um, but then I remember like life would be very different if I had stayed in that field. Again, like maybe I would have grown to like being a professor, but it just didn't didn't draw me in. Um, and it's, you know, it's hard to go like from postdoc to postdoc. You know, you're moving every year or three years, and you know, maybe eventually you get to be in a professor role at a university long term, but you know, you you don't really have a lot of say in where you live. And, you know, there's a there are certainly upsides. I would have loved to do research for the rest of my life. It would have been great and fascinating. But, you know, I I tried to find an alternative that was equally compelling that maybe offered me a bit more freedom in some of the other aspects of so how did you find data science? Yeah, when I was in grad school, I had several colleagues who graduated ahead of me and went into data science. And there were programs at the time that were like helping graduates from the STEM field kind of make that transition into into industry and be more, you know, business oriented, if you will. Um, and so I had a few friends go through that process and like hearing from them and about their jobs. It seemed like all the things that I liked about my research, like problem solving and coding, working with data and like looking for patterns and trying to figure out what's going on in the data, like what does that tell us? I really liked all those things about research, and all of that was also true in data science. So I started taking some classes, trying to figure out like what is what is all of this, and like, you know, learning um on the side so that when I graduated, I was a bit more ready to make that jump into into industry and that career change early on in my career.

SPEAKER_00 6:20

But I really like that you dove so deeply into what you loved, but it sounds like you weren't afraid to jump into data science, but I might just be assuming like, was it scary to do something different than what it was, yeah.

SPEAKER_01 6:33

No, it definitely was. And there, like I was lucky my graduate advisor, you know, after I graduated, paid for me to continue doing research for another six months or so, which allowed me the time to find a job and to go through all the interview process. But it was, it was, it's hard, like making that kind of career change. And I think it's even harder for people to do that now. I feel like I got kind of lucky at that time. But yeah, it was it was definitely scary. I there were times where I was like, I don't know if I'm gonna make it. Like, I don't think anyone's ever gonna hire me. Like there are there are when you're doing it by yourself, it's like it's very disheartening and discouraging. And eventually I did do a short program and with other people from STEM fields trying to make the same change, and like having that community definitely made it a lot easier. Like we were all going through the same thing together, trying to make this switch, trying to find a job, getting rejected from 5,000 interviews, you know. And you know, eventually I did get several offers and you know, picked up my first first job. So it worked out eventually, but it was definitely like a lot of doubt in those in those.

SPEAKER_00 7:39

So tell us, okay, so for people that aren't in this field, what does your job actually look like day to day?

SPEAKER_01 7:47

Yeah. And I'm gonna give two answers. One is like when I first joined versus like where I am now. And when I first joined, I was kind of entry-level data scientist type role. Like most of my time I was looking at data, I was coding analyses of that data, trying to figure out, you know, what's in the data, what does it tell us, what are the patterns, and then also building machine learning models off of that data, whether that was to, you know, get an insight out of what the different things are that are going on in the data or trying to predict what's next based on the data. Um, and so I spent a lot of my time just at my computer coding, you know, collaborating with colleagues here and there, um, and really just building these solutions, hands-on keyboard building these solutions for for the clients that I was working with. Nowadays, my job looks a little different. Uh, you know, it's been eight and a half years, so now I'm I'm leading different teams doing that work. So I'm not as hands-on. I spend a lot more time in meetings, but I spent a lot of time with clients to understand like, what are your problems? What are you trying to solve? Like, how could this be better? And then from my discussions with them, trying to understand, well, how could we build a solution that addresses that challenge? Like, you know, a client spending like a thousand hours every month reading contracts, like, how can we either automate that completely or make it a lot faster for them so they spend less time doing that manual, boring, tedious task. And that's what my teams are now doing is building those solutions to solve a particular problem for our clients. So spend a lot of times with clients, I spent a lot of time with my teams and yeah, across different projects that adds up to a good amount of meetings a day. So I spend a lot of time.

SPEAKER_00 9:29

Yeah, it's like, what is your job? Well, I sit in meetings, but yeah, for purpose. Yeah. I keep telling myself it's for a purpose. Yeah. Right, right. Because I I mean, I get it. My old job would just be meetings.

unknown 9:40

Yeah.

SPEAKER_00 9:41

Like what yeah, it's like, what did I do today? I sat in a lot of meetings, but a lot of meetings. A lot of meetings, but I think it's um it's also interesting. Like AI and machine learning. I cannot open gushing LinkedIn. That's everywhere. Yeah. Right. What have you what have you seen change the most in the field over the past decade?

SPEAKER_01 10:02

I mean, I feel like it's always been changing. And like my particular area of AI has always been natural language processing. So, how do we like take all of this text or audio or you know, it could be emails, it could be documents, whatever it is, to like make sense of it and make something, some process easier. And it always was changing year after year, even eight years ago. It's like what we were doing eight years ago, like seven years ago was so much better than eight years ago. Six years ago was so much better than seven years ago. But then, of course, the past couple of years has just been like crazy explosions. Um, and the technology has like the same problems that we used to try to solve back then are a lot easier to solve now, which is a good thing. But then at the same time, there's all this like hype in the market about like AI is magic and it can do everything, or AI is gonna kill us all. And like, I don't think either of those two things are right. I think it's probably somewhere in the middle. It's not gonna solve every problem, but it's also not gonna like destroy humanity. Like, I'm very practical, like it's somewhere in the middle. Like there are some things it can do, there are some things it can't do, you know. It is what it is, I guess.

SPEAKER_00 11:12

Yeah, I like that. And you know, the fear and the hype and all of it, you know, strong reactions to AI. What from your perspective, what do people get wrong about it?

SPEAKER_01 11:25

Yeah, I think one of the challenges in our current day and age is it's it's both a good thing and a bad thing. It's double-edged story, just how accessible it is. Like anyone can use it. You can just go to a website, whether it's ChatGPT or using anthropic with the Claude models, like anyone can just go and use it for anything. And that's good, like to have that level of accessibility for these tools. Like it shouldn't just be us data scientists in a back room that have access to it. But then the downside is that everyone has access to it and we see all this like AI slot. Um, and it's really about, I feel like it always comes back to the critical thinking of like, what are we using this tool for? And is it a good use of this tool or not? And then, you know, especially when we're thinking about my clients that are enterprise scale, like, what are they using this tool for? And is it a good use of that tool or not? Impacts a lot of people. And um, that's where like I feel like my team has the responsibility to go in and like educate people on what it can and can't do, what it is good for, what it shouldn't be used for, um, and bring that expertise with us as we're helping to build these solutions for our clients. I mean, that's harder on like an individual person out there basis, but for our part, you know, that's part of our job is to bring that that education along with us. And I think that's one one thing that's changed a lot is helping uh the people that we work with kind of see through the hype. Like there's all the hype, but what's real? What's actually realistic and responsible?

SPEAKER_00 12:52

Yeah. Doable, functional, helpful. Yeah, I really like that you talked about the critical thinking skills and using that and thinking through. And I'm also curious because you, you know, going from your deep PhD in astronomy, right, to solving business problems on a huge scale. What are the similarities and differences in the mindset between those two worlds?

SPEAKER_01 13:18

Yeah, that's such a great question. Yeah, I definitely think the critical thinking in both cases, and I I feel like that's something that I had to develop as a PhD of like how to ask questions of myself. Like if I'm doing something, I need to be the one like second guessing myself almost to put that rigor into my work. And that level of critical thinking is still really important in the space I'm in now. And I think the other thing that has become increasingly evident over the past couple of years is like the ability to teach yourself something new, because every day we get like the next iteration of these AI tools. And it's really hard to keep up. But being able to teach yourself new skills on just a constant basis is really important. Both as a PhD student, like I always had to teach myself something new and like read all these papers and try to understand what they were doing to see if I could use that same approach. But the same is true now in my role and like all of my team members of what's the latest and greatest thing? We need to stay up to date, we need to teach ourselves how to use it. And just because the tool is available, like we still need to know how to use it effectively and being able to use it and use it effectively are kind of still two different things. And so that kind of self-learning is still very important.

SPEAKER_00 14:31

Now, speaking of self-learning, like I remember when I talked to you the first time, I was shocked at how driven you are and also so humble. Thank you. To have that drive and like intelligence, deep, deep intelligence, and to have a personality that somebody can actually like really talk to and relate to you. And you speak in a way that I would say me being not a scientist or an AI expert can understand. I really appreciate. And you wrote a book. I did, yeah. Tell us.

SPEAKER_01 15:05

Yeah, well, it was kind of a funny story. I was at a conference with a colleague, and we were doing hiring. This was, I guess, about four years ago now. And our booth was next to a publisher's booth. And so we're we're sitting there and just like chatting with the booth next to ours. And my colleague turns to me and he's like, you know, we could write a book. Like we've gone through all these challenges and the work that we do with our clients. Like, there's a lot of lessons learned about, you know, the practical side of how you take all these algorithms and all this stuff that other books teach you. How do you actually apply it? And like, what are the challenges you run into? Like, we have a lot of knowledge just based on all these failures that we've had over the years, as well as successes. And so, yeah, it was just, I took all of that knowledge and like, let me write it down and put it in a book, and other people can can learn from that. So the book is about natural language processing, the kind of the foundation of it, but also going back to the critical thinking. What's the problem you're trying to solve? And how do you pick the right tools and the right approach and the right performance measurement based on what you're trying to do for a particular problem? Um, so yeah, just kind of took everything I've learned over the years and shoved it into a book. And I I also really enjoyed like the writing process and like the communication is important to me. Like, how can I explain this in a way that anyone can understand? Yeah, that was that was part of the goal too. Like, let's make it accessible. Like it doesn't need to sound like a bunch of jargony words. Like we can just explain it like normal people. Normal people. And what's next to the book? Oh, yes. The book is called Teaching Computers to Read. Um, because that's that's what I do. I teach computers to read text and make sense of it.

SPEAKER_00 16:44

And too, you are doing a lot of speaking right now, aren't you? Like on stage.

SPEAKER_01 16:49

I'm trying. So I have been doing different conferences and panels and things mostly over the past few months. The book came out in November. So just like trying to get the word out and uh, you know, share again, share that knowledge. It's in a book. Now I can talk about different chapters in the book to different audiences and um who might be interested in in learning again from all the mistakes and lessons learned that I've had over the years. So uh yeah, I have a couple more conferences coming up. And I just got accepted to Grace Hopper, which is like a big technical conference. I'm very excited about that in October. Um, yeah.

SPEAKER_00 17:25

Yeah. Congratulations. Thank you. You don't seem intimidated by anything. Is that you don't? Like you're just like, oh yeah, by the way, I'm gonna do this, I'm gonna do this, I'm gonna do that. Is that true?

SPEAKER_01 17:39

And how how do you know that's a good question? I feel like I do feel like that's maybe a skill that I've like been developing over the years. I that definitely was not always the case. Like when I was in high school and college and even grad school a little bit, like the thought of public speaking would have like turned me mute. I would have like been bright red from head to toe, like speaking at a whisper level. Like, but I think being in consulting forced me out of my comfort zone in a very good way that kind of like forced me to develop some of these skills that I maybe wasn't excited about. But then after you do them for a while, they just start to feel like second nature and start to feel much more comfortable. And now I I like to think that I can like to give me a new challenge, like I'll I'll take it on. I might not succeed, but like, yeah, let's take on a new challenge because it pushes me out of my comfort zone again. And then I'm like learning something new and I'm growing again. And that that does appeal to me in a way that it did not even like 10 years ago. But now it's like, okay, it's a new challenge. Like, let's do something different and learn something new. That's so cool. You just like the challenge. Yeah. I I like learning. And it's like, what better way to learn than to just go way outside your comfort zone, like writing a book or taking on a new role at work or you know, whatever it is, just like doing something different.

SPEAKER_00 18:58

I'm really getting the sense that you see failure as learning. I try to.

SPEAKER_01 19:05

Yeah. I can't say I I always succeed at that mindset, but it is that like growth mindset. Like if you have a growth mindset, that's what allows you to grow. So I try to reinforce that in myself. And also at this point, I feel like I've failed in so many things over the years that I would have liked to succeed at, whether it was like applying to this college or that grad school or like whatever it is, even at work, like, oh, we didn't get that client project. Like, I feel like I'm not that I'm totally numb to failure, but I feel like I've felt it enough that it's like that's fine. You just go on to the next thing. Um and and that's okay. Like it's fine. Yeah, it doesn't mean anything. You just keep going. Yeah, yeah, exactly. It's like you learn something from it, and then you take that with you to the next next thing. So again, not that failure doesn't get me down occasionally, because it definitely does, but uh I I think it's another one of those skills that like as I learn and grow, you gotta kind of like embrace it a little bit, even if it sucks sometimes.

SPEAKER_00 20:04

I love it. I love it. So, okay, so let's do a quick lightning round. Okay. Okay, so first answer that comes to mind. Okay. What part of yourself are you finally letting the world see? Locally, my weird side. I love it. I love it. Welcome, welcome to the weird side.

SPEAKER_01 20:25

Yeah, it's like you always put on that professional face, but it's like, no, I'm kind of weird. I'll just like make bad jokes and I don't know. I have like one TV show that I'm obsessed with, which is Futurama, which is like a totally dorky TV show. But any addition that there is any tangential reference, I'm going to bring it up. Good for you. It's just stuff like that, you know.

SPEAKER_00 20:49

Yeah. I love that. Good. Okay. What story or belief about yourself did you have to unlearn to step fully into who you are?

SPEAKER_01 20:59

That is a good question. I think that I'm capable, like kind of going back to our discussion about being outside your comfort zone and that failure is a bad thing. It's like, no, it's it can be part of the growth. And capable was the first word that came to mind because when I was younger, I didn't have a lot of like self-esteem or self-confidence. And I think that was part of the story is like, oh, that's just who I am. But like, it doesn't have to be grow.

SPEAKER_00 21:23

Not anymore. Yeah, exactly. Exactly. Right. Oh, not anymore. Okay. What does it cost you to be authentic? If anything, and why is it worth it?

SPEAKER_01 21:33

I feel like it definitely does cost sometimes when I don't know, I say something that I feel awkward about afterwards, like, oh, I shouldn't have said that. Um, but I think it's m it's to be authentic, I feel like cost is maybe mostly discomfort. Like the discomfort of being authentic in front of people that maybe don't know me very well. It doesn't cost me anything to be authentic in front of people I don't know very well. Or I do know very well, like friends and family, like it doesn't cost anything. But in front of people I don't know, it's a discomfort.

SPEAKER_00 22:02

Great answer. Worth it though. Totally worth it. Sorry not. Sorry. Okay. What boundary have you set that that protects your sense of self?

SPEAKER_01 22:12

For me, it's working hours. That's been a big, big change the past six months or so. But it allows me to get back to I have a book now. I need to spend time like thinking about that and getting at speaking opportunities and things, but also just like friends and family. Like that is a boundary that I need to hold myself accountable to keep for now on.

SPEAKER_00 22:35

Outside of work. Yes. I get it. Oh my gosh. Okay. If you could unmute one truth people are too afraid to say, what would it be?

SPEAKER_01 22:44

Man. Honestly, the first thing that comes to mind is just like inequity that people like to ignore. It's just that would that would be the thing. Like we're we're born into certain inequities, different people are.

SPEAKER_00 22:56

And just like, let's not ignore that anymore. Right. Love it. I'm here for that too. Okay. What keeps you grounded when you feel pressured to perform or fit in? Good question.

SPEAKER_01 23:07

Uh the first thing that came to mind was walking my dog. Just like we have our morning ritual. We go on a walk, just being outside, even if it's rainy or it's dark. It's just like this is important for my day, and it has nothing to do with anything except my dog and myself and starting the day. It's like, I feel like things like that keep grounded. Good for you. My dog doesn't care what I do at work.

SPEAKER_00 23:31

No, and your dog's just happy to see you. Exactly. I get that. Well, thank you so much. You're such a pleasure. Thank you, Jennifer. With love with listeners walk away remembering just one thing from this conversation. What do you hope it is?

SPEAKER_01 23:46

I hope that it is I think what we were talking about around getting outside of your comfort zone and failure. Like use that as momentum and not as an end point. Beautiful.

SPEAKER_00 23:58

And then on a more personal note, what is it meant for you to share your story today?

SPEAKER_01 24:04

Lovely. I feel like I tell these things to people, maybe one off here or there, trying to share my experiences. But I I really appreciate the opportunity to share some of what I've learned over the years to a to a broader audience and with you.

SPEAKER_00 24:17

I could ask you questions all day. We would go and deep dive on very obscure things and be great. We'll we'll schedule that separately.

SPEAKER_01 24:26

And then how can how can listeners connect with you and support your work? Yeah, uh, LinkedIn for sure. Um, I'm not really on any other social media at the moment, but definitely feel free to ping me on LinkedIn and let me know you listen to Jennifer's podcast and happy to connect and talk more there.

SPEAKER_00 24:44

Well, thank you so much, Rachel. And thank you to everyone listening for choosing truth over comfort, alignment over approval, and courage over silence. And if this episode resonated, share, subscribe, and stay with us as we explore what it really means to live and lead without muting who we are. Until next time, unmute yourself and be who you already are.