The Real Intelligence team sat down with Kristie Rowley, Principal Data Scientist and Director of Data Science at Domo, to discuss careers in data science. Kristie describes her career path as “meandering” and has worked in a variety of industries and positions throughout her life, until she came into her current role leading the data science team at Domo. She offers great career advice, discusses the importance of mentorship, talks through strategies for navigating various data science roles, and much more! 

Listen to the full episode on marketing data and analytics below, or wherever you listen to podcasts!

Interview Transcript


[Anna]: Welcome to the Real Intelligence podcast. You’re on with Jason Harper, CEO and Founder of RXA, and Anna Schultz, Marketing Coordinator at RXA. Our guest today is Kristie Rowley, the Principal Data Scientist and Director of Data Science at Domo. Kristie earned her PhD from Vanderbilt University and has worked as a data scientist and organizational behavior consultant for over 25 years. She has used data science and machine learning to effectively inform the business decisions and strategy of numerous organizations, including Fortune 500 companies, nonprofit organizations, governments and policy institutes.

Dr. Rowley also specializes in data science, machine learning, and artificial intelligence education. Throughout her career, she has designed and taught graduate level statistics, data science, and machine learning courses at numerous universities. She has translated this experience into her current role at Domo by working with organizations to effectively develop and scale up their production data science processes and practices.

Her work can be viewed in more than 25 peer reviewed research articles that demonstrate her passion for data science and its many real-world applications. Welcome to the show, Kristie!

[Kristie]: Thank you. So nice to be here. Thanks for having me.

[Anna]: Yeah, absolutely! So that’s an incredibly impressive bio, and I know it only kind of scratches the surface of your accomplishments in your career. So, we like to start off our podcast by getting to know the real you. So, I have a couple questions for you that we might not find the answers to in your professional bio.

The first one being, what’s the one thing you’d love to be an expert at?

[Kristie]: Oh, do I have to pick one?

[Anna]: You can give us a couple.

[Kristie]: Everything that I wanna try, I wanna be an expert at it. If I had to pick one, oh I don’t know. I think I would be, like, the world’s best guitar player. I think that’s what it would be.

[Anna]: That’s awesome. Do you have any experience with other musical instruments or just, kind of guitar?

[Kristie]: I grew up playing the piano, so I still play the piano today. I was classically trained in piano. Pianos are really hard to take to college and things like that, so I started playing the guitar when I was pretty young too.

I played a number of other instruments, but those are my 2 main instruments.

[Anna]: Awesome.

[Kristie]: And then in terms of music I like to song write and sing. So those are my 4 things in music, I guess.

[Anna]: That’s awesome.

Kristie’s career journey and ‘meandering’

[Anna]: My second question is, you mentioned to us in our previous discussion that you always wanted to be a lawyer and actually turned down a couple opportunities to attend law school. So, what kind of changed your mind and drew you to a career in data?

[Kristie]: Yeah. That is true. So, I am from a very, very small town in Idaho. And if you are an intelligent young woman, the 2 things that you can grow up and be is a lawyer and a doctor. Those are the 2 occupations that, you know are professional jobs when you grow up. So, I picked lawyer. Lots of jokes when I was growing up that I would make an excellent lawyer because I argued about things a lot, particularly with my father who argued right back at me.

So, I thought that that’s where I was headed, to law school, and I had 2 opportunities to go. That’s what I was going to do and just kind of decided it wasn’t for me. I did some internships with some law firms, and I got to shadow a few lawyers and found out that, while I was really fascinated about what they did, and I would absolutely loved law school, I don’t know that I would have enjoyed being a lawyer per se. So, I changed my mind and I went to academic route and started doing research a lot more.

[Anna]: Cool. That’s a really cool story to, kind of, hear what drew you to that path rather than, you know, it sounds like you had a lot of options that you could have gone down. So, you know, we do know that you did end up going down this route towards data and have made a really awesome name for yourself in that. So, can you start off by telling us a little bit more about yourself and your career journey?

[Kristie]: The word I would say to describe my career journey is meandering. I just meandered all over and tried to figure out where I would fit best. I think, partially, that is a function of being a woman, partially. I think that we often tend to meander a little bit before we get to where we’re going. We often grow up thinking that we’ll be in careers that might be gendered in some kind of way, and figure out that we have a lot of talents and haven’t exactly received the training or the mentoring along the way to propel us into a different career.

And so, I came to a place where I realized I can be good at a lot of things, and it’s really up to me to decide which one that I want to do and which one that I’m really passionate about. And when I figured that out, it was really freeing. That I wasn’t, I didn’t pigeonhole myself into anything. I had talents, I had abilities, I could use them in a whole bunch of ways, and I was fortunate enough to have a lot of mentors along the way that, whether they know it or not, and sometimes it was really insignificant things, they allowed me to believe that I could do things that I don’t think I would have come to on my own.

So, I’ve done a lot of things! I’ve taught English as a profession. I was a professor. I came to Domo, Domo made me an offer I couldn’t refuse, and I came to Domo about 5 years ago, which was a huge change from academia. And when you’re in academia, you kind of believe that academia is the best home you could ever find. And so leaving academia is really hard, and that was the most scary transition I’ve ever made in my whole entire life. And I made it, and it’s so much fun. It’s so much fun to be in tech, I love it so much.

So I don’t know. I meander. I meander a lot, and I don’t regret it. It’s not very streamlined, but I’ve learned so much at every step along the way. And I don’t know. If there are people out there who feel like they’re meandering, I wouldn’t necessarily discourage it. At some point, you do have to get a real job. And at some point, you do have to commit to something so you can propel yourself and be who you want to be. But it’s okay to figure it out first.

[Jason]: Well, I love that. And thank you, Kristie, for being a part of our show today. We are really honored to have you with us and talk about your meandering. I think that’s really good counsel too, to allow yourselves as you’re exploring careers, and learning who you are and what really interests you, to allow that sort of meandering. That’s a great way of looking at it.

And you’ve done a very effective job meandering through some really impressive jobs that anyone would love to land on. So good for you to continue to look for until you found something, you know, at Domo.

The link between creativity and data science

[Jason]: One of the things you said too that I found interesting, so your background, you know, piano, guitar, music. One of my kinda hacks for finding who’s a real data scientist is, are they musically inclined? Because if they’re not, then I start to question things. Those parts of your brain, from what I understand, are so, so interconnected. So, I wonder if you had any thoughts on that. Maybe tell us a little bit about how perhaps you feel music actually contributed to your career choice.

[Kristie]: I can only speak for myself, but for myself, I feel myself using the same part of my brain to write music as I do to come up with really creative mathematical solutions. I don’t know if that makes sense, most of us don’t feel ourselves think, maybe I think about it a little too much. But I feel myself using that same center of my brain to come up with scales and unique chording and things like that, as I do when I’m coding and writing unique mathematical solutions that we come up with here at Domo (that’s what we do, we do custom data science solutions). So, I feel myself using all of those same neural pathways to do that.

In terms of does being musical make you a good data scientist? I don’t know, it makes me a way better one. It makes me a way better data scientist because I can see how things piece together, not just in code blocks, but how they piece together in bigger stories. And so it’s absolutely made a difference in my career.

I think that it also exercises a part of your brain that is nice to keep open and not necessarily pigeonhole yourself, if you’re in a technical career. Data science is really weird, it’s not programming. So, if you’re a programmer, you probably can get away with just using one or two or a handful of neural pathways to get your work done. And that’s usually very effective for a lot of people.

I feel like when you are trying to create custom solutions, you can’t do that. You either have to hire people that fit each of those tasks or you have to be able to do it yourself. And I’m a do-it-yourself-er to a fault. This is not, I’m not bragging. This is, I wish I didn’t do so many things myself. But I do, I do, and part of that, I think, does have to do with being able to piece things together and just piece different aspects of your life together in a story.

[Jason]: Well, I think one of the things I say, probably too often, is that the dirty little secret of data science is that it’s more of an art than a science. And I think that creative, what you’re describing, that creative process and that methodology that you’re developing in writing music and that, probably does actually help train and think creatively to solve these custom data science solutions that you’re putting together for your customers. I think it probably does directly help. I agree with everything you’re saying there.

Bridging the gap between technical work and strategy

[Jason]: I think one of the other questions I have too is, I mean, you kinda touched on it. Being very hands on through your career, at least over the history that I’ve gotten to know you, you have an extremely technical role, but also a very strategic role. And you’re sort of straddling that back and forth between having to get in and be very strategic, and then implement and do things super technical. And so I’m wondering if you could maybe just talk about some of the methods or skills you use to sort of, like, bridge that gap to level up and level down, sort of as rapidly as you have to, probably oftentimes within the same day or even hour.

[Kristie]: You are right. I don’t think about that very often, so I’m glad you pointed it out.

Interestingly, we just took the Clifton strengths assessment as a team, and strategic was my number 1. It was my number 1 thing, and I love strategy, and I’ve always known that. I love it. If I didn’t have it in my life, I would probably wither and die. So I would not enjoy the data science role and getting down in the weeds and doing all of the technical things that being a data scientist requires, if I couldn’t be strategic. So I kind of do those technical, down-in-the-weeds things because I can, and I’m proud of the fact that I can do them. But what I really enjoy is the strategy.

I don’t know that I ever get away from the strategy. It’s always on my mind. My mind is always playing Tetris. Like, I’m always seeing the pieces fall and I, you know, sometimes 10 or 11 pieces that you haven’t seen yet, I know where they’re going to land and how that’s going to work out. And if I don’t get the piece I want, I can shift things around and make it work. So, I always have backup plans and backup plans to those backup plans, because I’m always thinking about strategy.

So, I like it. And I don’t think I move in and out of it. I think I always think about strategy. And I force myself to take breaks from it, because if you think about strategy too much, it’s really really hard to ground yourself into what’s important right now in the moment. So, I feel like I have to take scheduled breaks from being strategic. So hopefully, that answers your question.

[Jason]: I like that, that’s interesting. You need to give that rest or whatever to let yourself reset and take yourself out of it. And when you’re taking those brakes from being strategic, is it taking a break from being strategic and coding? Or is it actual rest?

[Kristie]: Nope. Yeah, not really. Not really. It’s just kind of retooling that strategy to get a different task done. Thanks for pointing that out. I’m less effective at this than I thought.

[Jason]: Fair enough. Something tells me you’re still highly effective at this.

Mentorship and building career confidence

[Jason]: I think, you know, kind of extending that a little bit further and circling back also to some of the things you talked about. Throughout your career, especially, you know, being a woman in a technical field, that mentorship component. And the advice that you got, or maybe didn’t get, along the way. And I think you’ve shared a few pieces of, I would say, wisdom for folks. But are there pieces of specific advice you would look to give someone, you know, from a generalized mentoring perspective for folks who are looking to either grow professionally in this space or perhaps make a career move into this space?

[Kristie]: I have so many different ideas on that. I’ll hopefully cover a couple. The first one, and something that we’ve talked about a little bit – I had a seventh grade teacher named Mrs. Geery. And she just, she saw that I was talented mathematically, and she believed in me. And she’s like, this girl needs to be in advanced math, she has to be in advanced math classes, they happen this year. She has to be in it, she’s really talented. And I was like, I’m gonna be a lawyer. Who cares?

But she really believed in me, and she believed in me so much that she called my parents in. She called me in. She called the principal in. And she made sure that happened. And everybody needs a Mrs. Geery, and I didn’t appreciate that nearly as much as a seventh grader. But I certainly did when I decided not to be a lawyer and decided to go into research.

I knew that I had talent in that area, and somebody believed in me in some point in my life. And that was the seventh grade, and you’re thinking, what does a seventh grade math teacher have to do, you know, when you’re 22 years old and you’re going to get a PhD? How does that happen? I can’t explain it. It just does. Having somebody believing you at some point in your life sticks with you for a really long time. So, one of the things that I would say is, find mentors that believe in you. And if you don’t have that…

Everybody needs a Mrs. Geery. Like, you have to have somebody who believes in you. And not just believes in you because, hey, you’re a great person, I believe in you because you’re great and you’re my friend. But believes in your skills and your ability to grow your skill set and your brain’s ability to be flexible enough to learn and grow into roles that you care about. So I think that would be the first one.

[Jason]: I would say, Kristie, on that too for folks as you’re thinking about that. I think that applies to both sides of the equation, and making sure that if we, as leaders, see people that we believe in, to make sure we communicate to them. Because I think there is probably a little bit of a lack of that communication of, like, knowing how to express when you see people that are amazing. And being able to articulate, and be that person for them who may not have had that in the past. So, it’s sort of like, not assuming that people have been built up, right? So taking the time as leaders to make sure that we recognize people.

[Kristie]: I think that’s a really good point, and to do it deliberately with them in the room, you know? I know that I champion my people. I have the best team ever, they’re so amazing. And I champion them all the time, but I don’t know if they’re always in the room while I’m championing them. And to give them that feedback, and let them know that that that’s how I feel about them, I think is a really critical piece. So, I love that. I should do better. So, thank you.

[Jason]: You know you’re awesome, right, Anna? I’m pretty sure I consistently tell you that.

[Anna]: Well, thank you!

[Jason]: And did you have anything else on the mentorship front? I feel like I cut you off a bit.

[Kristie]: I think the other thing that I would want to say to anybody who’s pursuing a technical role, especially in something like data science work. I think impostor syndrome runs rampant. It’s just rampant. Nobody feels like they’re good enough and everyone kinda feels like they need to peacock a little bit and always have all the answers. And I rarely find that that approach is helpful.

And I think, unfortunately sometimes, women experience that impostor syndrome even more. And sometimes, it goes in one of two directions. It’s either debilitating and you never get to where your potential lies, or it goes the opposite direction and you overcommit and oversell your abilities in ways that are off putting to a lot of people.

And I find that just being really honest about who you are and what you know, and being willing to learn and grow is almost always the best approach. In fact, when I interview people, one of my goals is to ask them questions until they say that they don’t know the answer. And if they don’t, if they never say I don’t know, then I don’t hire them.

So, they need to be humble enough to admit when they don’t know something, and also know how to deal with stuff when they don’t know the answer. You’re not always gonna know the answer. Like, my team is pushing the boundaries of what data science can do and what machine learning is capable of all the time, we always don’t know. I spend my time doing something every day that I don’t know. And if we can’t admit that, then I think it undermines our whole reason for pursuing and growing in the way that we have.

[Jason]: Can you maybe talk a little, I think part of being able to be humble in that regard, is allowing yourself to be vulnerable. And that requires a tremendous amount of confidence. And so, I’d be curious to know, how would you go about helping someone develop that confidence, who may even potentially be at a disadvantage because they feel like they may be being questioned and they may feel like they need to just exude confidence, even when they don’t have it. So can you maybe talk a little bit about that?

[Kristie]: One of the things that I like to do, especially with my brand new data scientists, is to surround them with amazing people. And the reason I think that’s important is because when they get on a call with a customer, when they’re interacting with key business stakeholders, where we need to be confident and we need to exude that confidence, they can kind of lean on their team a little bit. It’s a little bit of a crutch, so they almost don’t have to be super confident in themselves. They can be confident in themselves as being part of a group. And then they start to take on that identity of being very, very capable.

And then we can’t, I can’t keep them there either, right? You do that as a stepping stone. But ultimately, you have to get to the next step, to where they’re taking on assignments all by themselves and getting a lot of good feedback on that. And I think that that’s one place where leaders can fall down a little bit.

When I notice someone having confidence issues, and it’s time for them to have their own confidence on their own, one of the best things I can do is give them projects that they have to deliver on their own. And not to abandon them, like, let’s work on it together! Let’s do it together, but I wanna see what you can do. And then let’s set you up for a really, really good success story when you go deliver this presentation, or where you go to this customer meeting or you’re engaged in a rollout of a new solution.

So giving people responsibility and then helping them be successful in that responsibility out of the gate, I think is really key at helping develop confidence. And understanding that it’s not something that’s gonna happen overnight. It takes years and years to develop.

[Jason]: Yeah. I think that’s trying to shorten that cycle of years and years to develop. I think what you’re talking about there is just ways to help bring that confidence to a person sooner. I love that. I like the autonomy that you’re getting people too, to work through those projects where they’re still surrounded by all of that strength. I think that’s fantastic.

Methods to define success

[Jason]: I have perhaps a little bit more of technical question. So, one of the things that we often run into is, you know, how do we prove what we’re doing is working, right? So, like, prove that this is working. And so we’re constantly in this sort of, like, defending storytelling type of a mode when it comes to data science applications or even kind of more broader things in the business analytics world. So, I guess I would say, perhaps in your experience, what are some of the challenging or most challenging aspects of that? Maybe how are you addressing those?

[Kristie]: That’s a good question. Just a fundamental flaw in my personality is that I never think that I’ve done anything good enough, ever. I never think that what I’ve done is good enough. And I’m really trying to fix that because that’s not a good attribute of a leader to have if it rubs off on their team. The team needs to feel successful and the team needs to know when they’ve had definitive successes. But I myself, I’m always looking for different ways to do stuff. So I have the opposite problem of figuring out where we’ve won, and where we can do better.

One of the things that we always do after we wrap up a project is, we sit down together as a team and we talk about what worked, what didn’t work, what would we do differently next time? What would we like to do in the future? And it’s a really constructive conversation about if the team were set loose to do whatever they wanted, and maybe weren’t restricted by certain criteria of a project or scopes of projects or whatever it may be. We get to talk about what they want to do, and how they want to do it. And they have so many amazing ideas, way more amazing ideas than I have on my own.

We also have a culture on my team where, no, we seriously wanna know what we did wrong and we really wanna talk about it. Not because you’re gonna get fired, not because there’s any real high stakes about being wrong. But we always want to get better and if we love the thing, then we want it to be better. And the only way we can do that is if we talk about the things that we didn’t do great. So it’s part of our culture to do that.

But I also think it’s really important to just let go and I don’t let go very easily. But I need to, because you get so many amazing ideas from your people who are also amazing humans in so many ways. And it’s been just really humbling for me to learn from all of the people that I work with.

I say all the time that my friend group and my teams at Domo have been the very best, most talented, brightest, impressive people I’ve ever met in my entire life. And it is amazing to be around them and to see what kind of synergy happens when you let them talk about where they see their failures and where they see their strengths and how they want to grow.

[Jason]: Got it. I mean, I think, yeah, a lot of what you’re saying too, really comes back to the team that you’re with, and that you’re building, and that you’re a part of. So, I think that’s a really good, that makes a lot of sense. And I think too, one of the things you said, you never feel like your work is good enough, and I’ll just share from what I see. I’m constantly impressed and amazed by what you’re doing. So, from my opinion, it’s beyond good enough from what I’m seeing. It’s amazing.

Working at Domo

[Jason]: Kind of along those lines, I have one final question that I’ll put out there for you. So you work at Domo, can you share something that you love about Domo that folks like myself who don’t work there wouldn’t know?

[Kristie]: To me, Domo and being at Domo, it’s almost a feeling. It’s an attitude and it’s a feeling. It’s about doing our best work and being the most creative that we can possibly be, to be there for our customers, to give them the very best experience we can possibly give them. And that rubs off on the experience of the employees too.

It has been my extreme pleasure to work at Domo and to be able to hire really talented, amazing women and talk to them about what maternity leave looks like at Domo. And how family friendly Domo is, just in general. And so, all of that effort that we pour into our customers – it’s not because we come from 9-to-5, and check! We did our job. It’s because we love our customers, and that love of people rubs off on everybody at Domo, and we care about each other in ways that I haven’t seen at other companies. So that’s the thing that I think I really love the most about Domo.

Final words of wisdom – Create your own opportunities

[Anna]: Great. That’s wonderful, Christy. And thank you so much for joining the podcast today, for giving us your time, your advice, giving us some of your stories, some of the things you love about the company you work at and kind of how you got there. And a lot of the advice that you’ve shared for someone maybe looking to get into this space, or advance in this space, I think it’s really important for us to hear from people in positions of power that you really care, and you really do look to develop that in other people. So, thank you so much for sharing that and for your time. Is there anything else that you want to leave our listeners with today before we sign off?

[Kristie]: This has been a pleasure. Thank you so much for having me. I hope I’ve said some valuable things too.

The only thing I would say is, that if we’re talking to anybody out there who’s pursuing a technical role and maybe thinks that it’s not for them, or maybe thinks that they can’t do it, or don’t feel like they’ve gotten the right support to get to where they’re going. I would say if you’re passionate about it, stick with it. There are people out there who will help you. There are people out there who will help you navigate it. It can be challenging, but I think it’s really rewarding. And that you have to start often in places that you don’t want to start at. You often don’t start in the job that you want, you start in the job that is going to get you to where you want to be in 5 years.

And I think that today, people get out of school and they often expect to be in the job that they want to be in, in the next 5 to 10 years. And that’s often not what’s available, and that’s often not where you start. And it’s okay. It’s okay. Just take every opportunity that you get and turn it into the thing that you want.

I did not actually come to Domo as a Data Scientist. That’s absolutely what I am, but I came to Domo in a completely different role because I saw potential, and there were no data scientists at Domo when I got there. There was no data science consulting. There really was no data science part of the product. And so, take the opportunities that are in front of you and make them what you need them to be, to grow into the person and the professional that you want to be.