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College Graduate to Data Science
36 Plays11 months ago
On today's episode, I talk to Cole who is a Data Scientist at the National Research Group.
Cole shares how he got his first job being a recent college graduate and insight on how to maneuver the "needing experience to get experience" cycle.
If you have any questions for Cole or the myself, email us at [email protected]
Interested in finally taking the plunge by starting your career in tech? How does $1500 off a Springboard Career Track Course sound?
Use code EPEHT at checkout to save $1500.
Learn more here.
Edited by Dave Bianco
Cover art by Jerry Qu
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Transcript
Introduction to the Podcast
00:00:14
Speaker
Hey there, everyone. Welcome back to another episode of Life After Tech Bootcamp, the podcast where we dive into the stories of tech bootcamp grads and see how they've landed into the tech industry. By now, we've heard a ton about how our guests have used their past experiences to score tech jobs. But let's face it, not everyone's got a career history to bring to the job market. And yes, I'm referring to recent grads.
00:00:42
Speaker
I can completely relate to being a fresh grad back in the day. I had interned my entire senior year doing assistant level tasks, in my opinion, yet every interview felt like a broken record. They would tell me I lacked the experience for an entry level job because I was only an intern previously.
Struggles of a New Tech Graduate
00:01:02
Speaker
It was incredibly frustrating, especially taking the train from Philly to New York and having that told to me within 30 seconds and ending the interview right there.
00:01:11
Speaker
So moving on, I'm not bitter. Sure, experience like that is still gold, but even then it sometimes feels like it's not quite cutting it. And I can't imagine anyone who's never been annoyed by those entry level jobs demanding four years of experience. The job searching paradox is so frustrating and unfair and the whole needing experience to get experience, but how do you break the cycle? Well,
00:01:41
Speaker
We are going to talk about just that today.
Cole's Transition to Data Science
00:01:44
Speaker
And I'm so excited to introduce you to our guest Cole. Cole began his data science course after completing his undergraduate degree in cognitive science. And he's currently working as a data scientist at the National Research Group. Hi, Cole. Welcome. Thank you so much for being here. Hi. Yeah, thanks for having me on. Yes. And where would you like to share where you're recording from today?
00:02:10
Speaker
Yeah, yeah, absolutely. I recently actually moved to San Diego, so it's nice and sunny here today. I'm like you, I'm sure, being located in the Northeast. Yes, it is the opposite of nice and sunny. It is bitterly cold and getting dark at four, so definitely jealous. I've been to San Diego once before and I loved it. I should get back there at one point.
00:02:37
Speaker
Yeah, absolutely. It's a great location. Yeah. Well, anyways, okay. So you just got to San Diego. Clearly you're doing great things with your life, but let's go back to the beginning. You were in college. This is a bit different than other springboard students who came from a previous career, but you did this right out of undergrad. Yes. Yeah,
Entering the Job Market During a Pandemic
00:03:00
Speaker
that's right. Yeah. So I actually graduated in the spring of 2020 right at the beginning of the pandemic.
00:03:07
Speaker
and was really entering a job market that was
00:03:12
Speaker
not really, you know, there wasn't many opportunities for entry-level candidates, especially in, you know, competitive field like data science. And so, you know, I'd only had like basically one or two experiences while I was at college doing similar work. And so I was just looking for opportunities to get that experience, you know, without being able to get an entry-level position.
00:03:38
Speaker
Certainly. And with cognitive science, forgive me for not knowing my sciences. When I read that, I kind of thought that was something like a future therapist might get. Am I accurate on that? Or does that actually relate to data science?
The Interdisciplinary Nature of Cognitive Science
00:03:56
Speaker
That's a good question. So in short,
00:04:00
Speaker
Cognitive science is basically the scientific exploration of the minds, if you will. It's an interdisciplinary field incorporating or drawing upon a number of disciplines like psychology, neuroscience, philosophy, etc.
00:04:22
Speaker
So, you know, cognitive scientists are curious about how the mind works, functions and behaves, you know, asking questions like what is a mind? You know, how does, you know, your mind enable your conscious experience?
00:04:41
Speaker
You know, and many, many other questions, you know, could other non-human entities have minds and what would be sufficient to create a mind and say a machine, for example. But yeah, it was a really fascinating time getting to kind of explore those questions at an institution that actually had one of the oldest cognitive science departments. So I was really fortunate to be able to work with a bunch of esteemed professors there.
00:05:08
Speaker
That does sound really interesting. I would have no idea how to answer what is a mine. That question would just send me through a loop. But we don't have to talk about that now. You mentioned that you had some experiences in college. Would you like to share what those were?
00:05:25
Speaker
Yeah, absolutely.
Discovering Data Science Through Research
00:05:26
Speaker
So I was fortunate enough to be able to work as an assistant to some of the research or some of the professors in my department who were conducting research in the field. And that was really my first introduction to statistical analysis. And yeah, I guess in the vein of data science work, we were conducting experiments and using statistical models to
00:05:54
Speaker
to describe some of the patterns that we're noticing in the data. And yeah, it was, I don't know, one of the first things that I really got excited about, thinking about, oh, maybe I could do this as a career eventually. And yeah, that was kind of what introduced me to data science and got me interested in the field at large.
00:06:25
Speaker
That's fascinating. And, you know, still something worthwhile for experience. Like it kind of sounded like you fell down a rabbit hole a bit. Yeah, yeah, absolutely. I mean, yeah, you know, my experience was great in terms of, you know,
00:06:46
Speaker
Introducing me to a lot of these like skills and techniques And obviously the you know material the data that we were working with was really interesting to me I think the one thing though that I learned, you know at the accumulation of that experience was just that It at least in academia personally, I felt like it was a struggle to Work at the pace in which you know
00:07:16
Speaker
one works, you know, having to really like, dot your eyes and cross your T's and be very thorough and, you know, get
00:07:27
Speaker
peer reviews and, you know, sometimes papers don't get published for quite some time. And I just wanted to kind of move at a faster pace. And so that was what was really interesting to me about data science and industry, because there's, you know, it's such a fast moving field.
00:07:49
Speaker
And really like at the forefront of innovation for a lot of, you know, especially for a lot of these tech companies. And so, you know, I was really excited about trying to get involved in that kind of environment. Certainly, certainly. And I have heard academics, it is quite rigorous. And I have noticed a lot of people have shied away from it.
00:08:15
Speaker
But you wanted something more fast-paced. What was the connection you
Understanding the Ubiquity of Data Science
00:08:22
Speaker
made? You're working in these experiences. You're discovering how data is being analyzed. What was the link between looking into data science professions? Like how did you start to research that? Oh man, it was so long ago now. I think I, you know, I think I was in touch with a couple of the
00:08:46
Speaker
alumni from our department and recognize that there were some people who, you know, studied the same degree as I did and, you know, ended up going into data science. And so, you know, once I was introduced to that as a possible career track,
00:09:10
Speaker
Yeah, I kind of just wanted to learn more about it. I wanted to see what kinds of jobs are out there in that industry, of course, but also what kinds of industries are incorporating data science in their work.
00:09:26
Speaker
I came to find that it's such an exploding field, really, that most all industries are, in some way, shape, or form, trying to incorporate some of these newer, advanced statistical techniques into their work.
00:09:49
Speaker
The other thing I really was kind of yearning for, if you will, after completing my undergraduate degree was just getting some more hands-on experience doing those kinds of projects. In class, we talked a lot about theory and we spent a lot of time answering those kinds of complicated questions, some of which I mentioned earlier. But I was really curious about how to
00:10:19
Speaker
to really employ some of those ideas and build things with the tools that were at our disposal. And so that's actually really how I came across Springboard. And I saw that as an opportunity to, like I mentioned earlier, get some more hands-on experience. Certainly. And as you were describing this, I was like, man, it sounds like Cole wanted to build something.
00:10:46
Speaker
talking about theory for, it can be fun. I love it, but there is a difference between a thinker, I think, and a builder. But you answered that. So, okay, so you're wanting to build something. You've found springboard. I know you said in our pre-interview that you were really proud of the capstone project that you built. And I would love for you to share that story.
Capstone Project Experience
00:11:13
Speaker
Yeah, absolutely. So I came across a dataset specifically working with the Spotify API. They have a bunch of interesting data points about subjective features of music, such as a song's valence, like whether it's happy or sad or it's danceability. Yeah, there were several others, but it was quite interesting.
00:11:39
Speaker
what kinds of subjective features of the music that the data sets describe. So I wanted to see what I could do with that and I eventually decided to see if I could classify a song's genre based on these features of music. So I trained a classification model and it didn't have
00:12:04
Speaker
the greatest accuracy as there's a lot of overlap between these kinds of features and certain genres. And so I eventually, I believe I took the artificial intelligence and machine learning track within the data science course. So I was learning about
00:12:23
Speaker
some of those more advanced techniques such as natural language processing and ended up employing some of the things that I learned there to calculate the sentiment of a song's lyrics and adding that as a feature to the model which improved the accuracy significantly. So that was a really cool project kind of getting to build upon, you know,
00:12:47
Speaker
in kind of a rough draft or a prototype and seeing where I could access more information that would get at what I was trying to accomplish at the end of the day. Certainly. Yeah, I would imagine that would be really challenging. I was reading a little bit about Nirvana and their music history and
00:13:10
Speaker
I'm not a music aficionado, but yeah, you would on the surface classify them as rock, but then it's grunge, but then curcumin really wanted to pop sounds. So I wonder, I'm just out of curiosity, did you classify it by maybe like rock and then have sub genres below it?
00:13:32
Speaker
Yeah, so I did keep the categories of genre at a fairly high level, just for simplicity's sake. But yeah, I mean, you could certainly take that idea and run with it. There's so many subgenres of music these days, and each of them are really unique in and of themselves.
00:13:57
Speaker
Certainly. Very, very cool. Well, so that's what you did through springboard. Um, was there anything specific within the course that really helped you that you're employing today? Yeah. Um, yeah, that's a great question. It's interesting because, um, the, the first job that I landed after graduating, um, actually I didn't really employ most of the skills that I learned in springboard.
00:14:25
Speaker
We had a specific set of software that we used at our company, and the job's responsibilities were distinctly different from that of a traditional data scientist. It was more of a junior-level data analyst role. But since then, I'm actually
00:14:47
Speaker
I've actually taken up the responsibilities of the data scientist role at this company, and I'm using a lot more of the skills and techniques that I learned at Springboard, which is really exciting.
Climbing the Career Ladder
00:14:59
Speaker
So that sounds like a very coy way of saying you got promoted. Yes, that's right. Well, congratulations on that. We had another episode previously talking about career progression and just having the patience to maybe not do exactly what you think where you took an analyst job and eventually growing into data science. So I can't imagine how rewarding that feels.
00:15:28
Speaker
Yeah, it's definitely very rewarding. Yeah, thank you. Absolutely. And so did you do anything outside of the course to really prepare you? At the time, I did maybe one or two other courses specifically, actually, with wanting to learn more at the time when I was working on my
00:15:56
Speaker
capstone projects, I wanted to learn more about natural language processing. And so I found another course, more of a hands-on walkthrough of how to implement some of those kinds of techniques that was really helpful in finishing that project up. But yeah, I did do my best to really just stick to the curriculum. And I knew that in such a short amount of time,
00:16:24
Speaker
I knew that I wouldn't really be able to master any of those skills and that I really was going to have to continue to work with those things and learn more, especially like I mentioned earlier as this industry continues to evolve. But yeah, I found it easy to get distracted and so I learned
00:16:47
Speaker
very quickly that it was best just to try to power through the course and complete it in one fell swoop. Certainly, certainly. So you're finishing up the course and you're starting the job hunt.
Job Hunting Strategies Post-Bootcamp
00:17:05
Speaker
What was that like? Yeah.
00:17:08
Speaker
So, you know, I really, I really enjoyed working with the career counselors. I think, you know, part of the struggle prior to, you know, to joining the springboard bootcamp when I was applying for jobs post-graduation was that I didn't really know what I was doing. You know, I didn't have
00:17:31
Speaker
Any affirmative feedback like oh, this is you know a good resume. This is a good cover letter You know to use it the right kinds of jobs to apply for and all that kind of stuff I was really just shooting in the dark
00:17:42
Speaker
And that can get discouraging, especially when you don't hear back from a lot of these jobs, given it was a poor job market at the time, especially for entry-level candidates. But that was really helpful to be able to work with the career counselors in my experience and have a certain expectation as to how I should go about the job process.
00:18:13
Speaker
They provide some guidelines as to how many jobs you should apply for on a weekly basis and how many networking connections and et cetera. I reliably met those or exceeded them. And yet, for the first couple of months, I still really didn't hear back from many of the jobs or at least didn't land an interview.
00:18:38
Speaker
But, you know, I was ensured that it's a high volume strategy and just to have faith in the process.
00:18:48
Speaker
I think they at the time informed me that something like 95 or so percent of springboard graduates land a job within six months. I don't remember if that was the exact statistic or if that statistic has changed, but that was really encouraging knowing that this process works for almost everyone who graduates the program.
00:19:12
Speaker
I kept at it and eventually I did land a couple of interviews, one of which with the company I work for now. And interestingly enough, I wasn't aware of the job opportunity prior to
00:19:29
Speaker
Prior to applying, I was actually contacted by a recruiter who was employed by the company. And he had actually seen my LinkedIn profile, which the career counselors helped me cultivate in order to really describe who I was and what kinds of opportunities I was open for.
00:19:56
Speaker
Yeah, it was definitely, definitely a great experience. Fantastic. So I'd love to know, well, I want to know a lot of things, but first question, did you apply to jobs after you finished undergrad or what was that gap between like,
00:20:14
Speaker
I did, yeah. I spent the bulk of the summer applying to jobs. And like I mentioned, just did not have any luck whatsoever. And so that was really one of the motivations for seeking out a program like Springboard, especially because I wasn't in a position to go back to school, get a graduate degree. And it seemed like a great alternative
00:20:43
Speaker
As well as, you know, being much more of a hands on learning experience, you know, a project based curriculum, which was, you know, that was something I felt like I was lacking during my undergraduate degree. So, yeah, that was kind of.
00:20:59
Speaker
you know i i think i may have even set like a deadline for myself like okay if you know if you don't hear back or get you know certain number of interviews and the certain number of time then maybe consider like you know going and um accumulating more experience to add to your resume.
00:21:17
Speaker
Certainly, certainly. So great point experience, right? You know, coming out of undergrad, you don't have years of a career experience. So what did the coaches kind of help you with to really bulk up your resume to say like, Cole can do this job?
00:21:36
Speaker
Yeah, I mean, of course, like adding springboards, the resume, it was the first thing that we did, but also not just, you know, the fact that I had graduated the bootcamp, but also some of the specific projects that I had worked on as well. And those were
00:21:52
Speaker
It ended up being major talking points in the interviews that I did land because they had seen that I was able to do the job that they were hiring for. I wanted to know what my experience was doing that. It wasn't necessarily something that I realized you could do, I guess.
00:22:11
Speaker
uh, joining springboard, I just kind of assumed that, um, you know, under the experience sub header, it had to be actual, you know, paid positions, but, um, that's not necessarily the case. And, and, um, that was definitely, uh, a huge, um, added bonus to, to the resume. Certainly. And I'm curious, I know there's a bit of a stigma with boot campers in general. Um, people complain that.
00:22:40
Speaker
they just have cookie cutter portfolios, projects. I know that's definitely the case in UX design. I'm curious to know what that's like for data science. But you said that those projects were major talking points. So would you be able to elaborate on that?
00:22:59
Speaker
Yeah, absolutely. That's a great point. And I think that can happen. But, you know, especially when I was choosing my capstone projects, I was advised to pick something that I was interested in, maybe something that even was related to my background, for example. And I found it easy to
00:23:21
Speaker
Talk about those projects and interviews simply because I'm a music fanatic, you know, so I find that to be
00:23:33
Speaker
something that I can really not only be passionate about, but clearly describe the problems at hand and the solutions to those problems. In my case, I was curious about classifying genres of music, given this data set and trying to find a more accurate
00:23:59
Speaker
information to describe this music in order to accomplish that task. And so, yeah, I would recommend to any boot campers out there or others who are just working on personal projects to pick something that they're interested in and have a problem that they're passionate about solving.
00:24:21
Speaker
Certainly. And that definitely is an extra flair to make you just sound more passionate about the job you're interviewing for. Yeah, absolutely. I mean, I also find it, you know, I totally agree. And I think I also find that it is
00:24:41
Speaker
Easier to get invested in the project in and of itself if it's something that you're interested in, if you're motivated to solve the problem at hand.
00:24:51
Speaker
Whereas, you know, if you're working with one of those cookie cutter data sets and, you know, I found that they all have cookie cutter projects for UX too. And I see the same projects over and over again. And there's only so much you can do with something that's somewhat pre-made. But going back, what else helped you with landing a job?
00:25:29
Speaker
I mean, in my case, the job that I landed, you know, like I mentioned, was due to the fact that the recruiter reached out to me. So, you know, I may have underestimated it at the time, but really curating your LinkedIn profile to
00:25:46
Speaker
really communicate like who you are and what kinds of opportunities that you're looking for is certainly an important thing. I found like networking really helpful as well, you know, and not just, you know, looking for referrals to, you know, openings at their companies, but more so just learning about their experience. And what I found is that everyone has, you know, really a unique journey that led them to their, their position, their current position or, you know, that
00:26:15
Speaker
guided them along their career growth and career path. And yeah, there isn't necessarily one universal, you know, set of steps that everyone follows in order to land where they would like to necessarily. And so really just being open-minded to opportunities and
00:26:45
Speaker
Yeah, staying connected with people in the community. Certainly. So tell me about this recruiter that reached out to you for the job that you have now and you've also gotten a promotion in.
Landing a Job Through LinkedIn
00:26:57
Speaker
What was that experience like? You know, I actually moved pretty quickly. I was waiting to hear back
00:27:04
Speaker
from another interview when I was contacted by the recruiter. And he told me a little bit about the company, said that they were looking for someone with my skillset to join the data science department. And that if I was interested, then he could set up an interview for me. And so I ended up interviewing with my manager as well as the head of the department
00:27:34
Speaker
after which I got an offer. It all happened very quickly. I'm sure that's the case for many others in the job searching process, but I ended up feeling really good about it. The company is really interesting to me. I love the work that I do and the kinds of problems that we try to solve. It just felt like the right opportunity for me.
00:28:02
Speaker
Certainly. So I'm confused because when we talked about what skill sets you're using in your current job versus what you learned at Springboard, you said a lot is different. So I'm curious to understand what the recruiter meant by we need your skill set, but then you've learned completely new skills on the job. Yeah, so
00:28:26
Speaker
Yeah, that's a great point. So really, you know, at the end of the day, a lot of the things that I was doing in that junior level analyst role was quite similar to
00:28:41
Speaker
you know, it was the same kinds of analyses, if you will, that, you know, we were using or we were performing in the bootcamp at Springboard, just we were just using different tools. So while I was, you know, at Springboard, we learned how to implement these kinds of analyses and train these kinds of models and
00:29:00
Speaker
In Python, in my initial role, we used some statistical softwares to conduct these analyses, as well as some newer analyses that were more specific to the market research industry. Interestingly enough, when I was in my interview with my manager at the time,
00:29:30
Speaker
Um, she asked, you know, Oh, well, have you ever used these programs or have you ever, you know, conducted these, these analyses? And I said, you know, I, I haven't, I actually haven't even heard of them before. And she was like, Oh, okay. Well, would you be willing to, to learn them? And I was like, yeah, of course, you know, I'd be happy to learn them.
00:29:49
Speaker
And really, I think that that willingness to continue to learn really went quite a ways for me, at least during that interview and into my job as well.
00:30:03
Speaker
You know, I didn't necessarily have to have it all figured out by the time I graduated
Springboard's Educational Philosophy
00:30:08
Speaker
springboard. It was it was, you know, only a six month long course. There was no way I was going to be able to master all these skills and other skills that were specific to this industry that I was entering. So, yeah, I think I really tried to employ that mindset.
00:30:26
Speaker
you know, throughout my career as short as it's been thus far. But, you know, it was certainly helpful for me to end up landing the data scientist role recently. I think like Springboard's philosophy, or at least I remember
00:30:47
Speaker
a representative from the company talking about this at one point. I forget where it was, but I think their philosophy is essentially to have you do the job that you want to do before you are doing that job. Like I mentioned earlier, it's a project-based curriculum.
00:31:07
Speaker
And we're employing a lot of these analytical techniques and training a lot of these machine learning models and whatnot that we would eventually be doing in the jobs that we wanted. And so I kind of took that philosophy to heart at my job and ended up trying to get involved. Once I was a data analyst at the company that I'm at currently, I did try to get involved in
00:31:36
Speaker
in whatever ways that I can with the more stereotypical data science work. And that ended up being not only a great learning experience for me, but really a catalyst for to end up moving into that role eventually. Certainly. And I think my favorite part of that story is that your manager actually wanted to teach you stuff.
00:32:05
Speaker
And in my experience, I found that there's certain things that can be taught, but a lot of the times if you don't know a certain program, you're next. So what was that like, you know, getting the opportunity to learn with your manager? Yeah, absolutely. Um, it was, it was, um,
00:32:28
Speaker
not like something that I learned right off the bat by any means. I was fortunate enough to be given opportunities to conduct some of these analyses that were newer to me, make mistakes along the way, be corrected.
00:32:45
Speaker
And a lot of that, you know, it was self-taught, you know, there are obviously resources online, but also it wasn't like someone was like walking me through that process. Like I mentioned, you know, really that willingness to learn is something that, you know, comes from within, right? No one can force you to do it. So, yeah, that was, you know, I ended up picking it up
00:33:13
Speaker
eventually and I was in that role for, let's see, I think about a year and a half. So I learned a lot along the way. And a lot of that experience, I didn't obviously get to learn when I was at Springboard. It's a lot of domain expertise for the industry that we're in, but also learning how to work within a corporate environment.
00:33:41
Speaker
learning how to satisfy your client's needs and expectations and how to meet the expectations of your stakeholders internal to the company and communicate a lot of these more advanced analyses in simplified terms and all these kinds of things that
00:34:08
Speaker
Um, I really appreciated getting that experience, um, because, you know, I, I was able to learn how to do those, uh, you know, learn how to acquire some of those soft skills and, um, that, you know, I, I continue to use today in my new role. That's fantastic. So just about your new role, what's your day in, day out like? Yeah, absolutely. So, um, you know, we, um,
00:34:38
Speaker
I guess I should start by saying, you know, National Research Group is a, you know, we're a global insights and strategy firm. We work in the market research industry and with clients primarily in the entertainment and technology verticals, you know, some of the leading Hollywood studios or streaming providers or social media companies, et cetera.
00:35:08
Speaker
And we do custom research, both qualitative and quantitative for these clients. And so as a data scientist, I'm working primarily with the quantitative research data, which we collect via surveys.
Role at the National Research Group
00:35:23
Speaker
I'm using this data to build predictive models, classify target audiences, and even develop internal tools to assist some of our client-facing teams to help deliver actionable insights to our clients.
00:35:46
Speaker
insights about what their consumers' needs are or what their brand strategy might be, where they or their products fit in amongst the competition and what sets them apart, all kinds of different questions of that nature. So yeah, it definitely changes from day to day, but yeah, it's really exciting to be a part of.
00:36:16
Speaker
Certainly. So do you work with one client at a time, your team, or are you managing all the different clients at once?
00:36:24
Speaker
So in my previous role, I was working a lot more as a data analyst. I was working with several clients at the same time conducting some of the advanced analyses for their custom market research. Now, as a data scientist, I'm actually working with some of our syndicated products, some of our recurring surveys that, you know,
00:36:54
Speaker
keeps a pulse on some of these different industries that our clients are in and that we're interested in in general. So I'm not necessarily working with clients as much anymore and rather kind of assisting some of our other client facing teams in whatever way that we can.
00:37:18
Speaker
Certainly. So what would you say is your favorite part about your job? That's a great question.
Excitement in Market Research
00:37:24
Speaker
I think I really love the fact that in market research in general, and specifically on my company, we get to have our hands in a lot of pots between all the different clients that we work with, all from different industries, as well as
00:37:48
Speaker
all the different things that we get to do from day to day basis. We're a relatively small department at the company. Our main product isn't necessarily artificial intelligence or machine learning. The data science department is more of an auxiliary function to the larger company.
00:38:14
Speaker
And so, you know, as I'm, as the sole data scientist in our department, um, I ended up like helping out with some of the responsibilities that you might describe as falling under the scope of, um, data engineering or
00:38:32
Speaker
of, you know, MLOps even. And really getting opportunities to learn about all these different kinds of skills and sub fields within data science, if you will, has been really exciting to me as well.
00:38:54
Speaker
That's very cool. Yeah, I think that goes along with your willingness to learn and being able to have your hands in different parts of the scopes. With that, I'd love to understand, you're in this great job, you've just got promoted, where do you see yourself going next? Yeah, it's definitely a good question.
00:39:21
Speaker
I'm not totally sure. I think I'd love to continue to soak up all the learning experiences that I'm getting currently, really in efforts to become more of a full stack data expert, if you will.
Future Aspirations as a Data Expert
00:39:44
Speaker
And yeah, I mean, I think I'm really happy where I'm at currently. Like I mentioned earlier, I love the work that I do. And I feel like I'm continuing to learn on a daily basis. But yeah, who knows where the future will take me. That's fantastic. And I think it's totally fine to not know.
00:40:07
Speaker
I mean, it didn't sound like you knew you're going into data science when you were in college, you just discovered it. And I think that's what that willingness to learn really helps carry you through. So it's, I think it's okay. Yeah, I can agree more. Certainly. Well, since we're coming up on time, is there anything else that you didn't get to talk about that you really wanted to share? Not necessarily. No. I mean,
00:40:36
Speaker
Yeah, I don't know how traditional my experience, my job search was, but if there's any advice that I could share to people who are in that process currently, or perhaps in the middle of the bootcamp, I would just say to have faith in the process. And yeah, to just be open-minded to whatever opportunities may arise.
00:41:03
Speaker
Certainly. And I think it's funny that you say traditional job search process. I feel like a lot of guests have touched upon that, whether they spoke about that in their episode or just to me privately. I don't know what the traditional job search would look like. I don't know what that is. So if somebody has a definition for that, please let me know. I would love to talk to you about it. Well, fantastic. Would you be open to listeners connecting with you on social media?
00:41:33
Speaker
Absolutely. Yeah. Feel free to find me on LinkedIn. Just as I reached out to many springboard graduates when I was enrolled in the bootcamp, I'm always welcome if people want to reach out and chat. Certainly. And Cole, would you be able to share the spelling of your name so people aren't adding the wrong Cole? Sure. Yeah. It is C-O-L-E. And then my last name is L-A-N-D-O-L-T.
00:42:03
Speaker
Well, thank you so much for sharing your story and for all your time today. I think this is definitely insightful for people who don't necessarily have a background to leverage when switching careers. Sometimes you just need to get started. And I did want to share for anyone listening, if you have any questions for Cole or myself that could be answered on a future episode, please email me at alumnipodcast at springboard.com.