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VOICEOVER: This is Alumni Aloud, a podcast by Graduate Center students for Graduate Center students. In each episode, we talk with the GC graduate about their career path, the ins and outs of their current position, and the career advice they have for students. This series is sponsored by the Graduate Center’s Office of Career Planning & Professional Development.

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JACK DEVINE, HOST: Welcome to another edition of Alumni Aloud. We are here with Paul Schweigert. Thank you so much for joining us.

PAUL SCHWEIGERT, GUEST: Thanks for having me.

DEVINE: Alright, so you’ve a little bit of a different path than some of our guests. You did not finish your PhD at the CUNY Grad Center. So when did you realize that academia wasn’t right for you? Was it a difficult decision to drop out of the History Department?

SCHWEIGERT: So I remember kind of exactly when it was. It was at the Society for French Historical Studies Conference in Montreal in April of 2014 I think. I had given a talk that morning that you know, okay, crickets. And then so I was a little bummed about that and that evening they had the reception and so you know a couple hundred people in this giant room, you know, wining and dining and that kind of thing. I had gotten there early and I was talking to a few people and I remember kind of sitting there thinking you know this isn’t for me. I just kind of had the realization like in the middle of a conversation. So I excused myself and kind of left, found some little dinner in the outskirts of Montreal, had some greasy eggs and was like okay, I’m done. You know it took me a while to kind of, you know, but that was when I had like the, kind of something just clicked in me at that point in time like I was like this isn’t for me. So yeah it kind of came all at once there. 

DEVINE: Was it a difficult decision to drop out once you had that epiphany at that conference in Montreal?

SCHWEIGERT: It was, It wasn’t difficult. It was more difficult to figure out, I mean, so when you’re in a program I feel like you know what you’re working towards and once I decided that I didn’t kind of wanna you know finish the degree, and do history. And I was like okay what am I gonna do now? And that I think was the hardest thing is figuring out kind of what did I want to do because you know it was, I had spent, I don’t know, six or seven years at that point working towards something that I wasn’t gonna do anymore. So I think that was the hardest part of moving on was like, actually making a decision, okay what am I gonna do now and how am I gonna support myself outside of, you know, teaching which I had been doing for six or seven years. 

DEVINE: So the big challenge was the change up, so figuring out what you were gonna do next. So when did you first make the decision to pursue a career in the private sector? And what steps did you take along your path to end up as a Senior Software Engineer at IBM? 

SCHWEIGERT: Yep so I had, so when I was an undergrad I was actually originally a mathematics major and I switched to history kind of about halfway through. I still got a minor in mathematics and you know still had some of those skills. So I had always kind of had a little bit of regret that I hadn’t gone down that path and so that was kind of what I decided what I wanted to do. I wanted to go back and at the time I was really interested in mathematical modeling. How do you take mathematics and numbers and statistics and build a predictive model out of it. So okay so that sounds like fun so how am I gonna do that? Coming from someone who has, you know, a degree in history. They don’t, you know, quantitative places don’t tend to hire a lot of you know, historians. What I end up doing is this neat thing at the Graduate Center that you can take courses at other schools throughout CUNY if your advisor signs off on it. And so I actually took a bunch of or retook a bunch of undergraduate mathematics courses. So basically, to start working through the prerecs. So I basically figured okay I need to have some kind of mathematics or STEM type degree to do this. I looked around CUNY, either a bunch of kind of you could get in applied mathematics at a couple schools at CUNY so okay let me go take some classes. Start building up kind of the knowledge base so I could kind of make that transition and so I was kind of fully prepared like I’m gonna go earn another degree, spend some time you know and you know get the degree and come out and find a job. And so I think I did that for about a year and at some point I got an email from the Professional Services office that IBM was coming recruiting for marketing. I was like okay I know IBM, my dad worked for IBM, I’d like to work there. So, you know, I crafted a resume. Jenny helped me kind of get a resume together. Did the interview. Applied. Talked to three different people. Ran through my background. They decided okay we’ll hire you as an intern. So that kind of answered that question for me. So that’s kind of how I got in. 

So how did I go from an intern to a Senior Software Engineer. When I got hired in Marketing I got hired in what they called an Analytics Consultant which was essentially doing basic kind of statistical analyses on kind of static data so you have a big table of data, you know, you do some, you know, find the mean of this column, find the median of that column, minimums and maximums and try to make business decisions based on some of the statistical insights that you’re pulling out. So I did that for a while, you know, I did an internship. You know, I did an intern project that summer, did well on that, got hired full-time that fall. And started kind of doing that same thing but you know that, I really wanted to get more into kind of like the modeling aspect of it. And so, while I was, it was basically like I had a project, you know I could’ve done it like the simple way but I decided like okay I’m gonna learn Python and I’m gonna write this up in a script that I can then automate and then use to build some kind of model off of it. Do some modeling on the data. Starting kind of teaching that, learning that in my spare time and as a result of that I got picked up actually for a different project that needed those skillsets for what we were doing some sort of real big data analyses on media data like display banner ads and that kind of thing. And so that got me kind of into the data science realm proper. So I worked on that project for a while. In the course of doing that it turns out that what was needed to kind of for that was less of the analytics and more of the programming side. People kind of had to do platform type work. So I ended up moving from that project actually into our platforming engineering team at IBM. So instead of writing the models I was writing the platforms that the models ran on top of. So that got me into a bunch of ways to run software, especially software at scale, starting learning about containers and kubernetes, cloud data software and the kind of thing. Which is ultimately moved me to where I am now where I pretty much work out in the open-source cloud native world, exclusively. So in things like kubernetes and K-native and projects like that, that are for building sort of cloud first software. So, yeah that’s kind of how I got from point a to point b. A lot of looking for, you know, taking account of what my current role was, what do I wanna add on to this, learning that stuff, then kind of finding an opportunity where I could do that which kind of helped me advance up the ladder there. 

DEVINE: So it all started when you discovered you had this passion for math, or mathematical modeling and you took advantage of CUNY’s resources to sort of expand your credentials and then you found an opportunity, had Jenny at the Career office help you out, then you got into IBM and successfully worked on project after project to get to where you are today. But while you were on that path were there any other career options that you considered? 

SCHWEIGERT: Not really. I mean I would think within you know computer science I looked at different ways that I thought about going more hardcore kind of analytics or statistical, you know there’s all kinds of things in software development. There’s front end and back end. But I really just kind of, you know, I took what I had or where I was and if there was something kind of tangential to it that I was interested in I tried to learn about it and see if I could fit it in to that kind of thing. So it really wasn’t about a whole different bunch of options. It was more kind of, okay, I’ve got something now that’s letting me pay the bills and you know live and that kind of thing then let’s see if I can add something to it and if there’s a direction I want to pivot in. 

DEVINE: Sounds great. So you had multiple experiences in the CUNY system. You first were in the History Department. You were there for several years. Then you also took advantage of the mathematical courses that were available within the broader CUNY system. So what role did the Graduate Center and the CUNY system as a whole have on your intellectual development and how did your experiences at the GC and in CUNY transform you into the software engineer that you are today? 

SCHWEIGERT: Yeah so, it’s a bit of a hard question to answer you know. I grew up, so to speak, at the Graduate Center. I came in my mid-twenties and then left in my mid-thirties. So I did a lot of, you know, went through a lot of life lessons during that time. So I think it played kind of a large role. There’s also other things I would say that kind of CUNY helped shape and graduate school helped shape was the idea of kind of managing multiple things at once. Like as grad students we’re taking classes, we’re teaching, we’re doing research, we’re doing work study, we’re a research assistant for somebody. And you got all those things going on all at once and you have to deliver certain things at certain times. I think that played kind of a large role that helped make me successful later on was just learning how to do all that stuff in that environment. And the other piece that I’ll call out is teaching I think. Which we do a lot of at CUNY. I think also played kind of a fairly large role in kind of my development. You know having to plan and take ownership of a course or multiple courses often times at multiple schools over the course of you know the multiple semesters that we teach. Having to mentor students, speaking in public, all those kinds of things I think really helped me kind of develop and mature into the person that I became. So it’s less I would say the intellectual piece, I don’t do a lot of intellectual work these days, what I would consider intellectual work these days, but I think that said the Graduate Center still played like a fairly large role in developing me as a person if that makes sense. 

DEVINE: Yeah absolutely. It was these skills that you developed juggling multiple tasks when you’re working as a graduate student whether that’s a research assistant, as a teacher, doing research on your own, taking classes, the sort of multi-tasking that has to go on in that position and also the leadership that emerges from teaching, working with students, having this kind of large presence within a classroom. So you took those skills and you translated them to your at IBM. What were some of the challenges you encountered as you transitioned from graduate school to IBM? How do you handle the transition from history to STEM?

SCHWEIGERT: Yeah so challenges transitioning. I’d say the first one that I experienced particularly when I was interning was that I was the only intern over 30. So kind of the age difference going back into kind of like entry level positions was a bit of a shock. It was kind of something you kind of make your peace with. I went from being, you know, ten to fifteen years older than everybody that I was teaching to you know working for people who were ten years younger than me. So that was, took a bit of getting used to just just in terms of resetting the mental model a bit. So that was one challenge. The other kind of challenge was particularly from someone who didn’t do an undergraduate or a graduate degree in computer science I always kind of feel like there are things that either I don’t know or you know, a background that I’m missing or that I have to go out there and learn because I assume that everybody else knows all of these things. So that can be a challenge. I think one of the ways to mitigate that one is to remember that, you know, particularly after you’re out of, you know, particularly after you been at it for a while a lot of people don’t remember everything that they learned in school. And so you may not have experienced it so you’ve had to go out and relearn some of these things or learn these things for the first time, you know it really helps you because you kind of have to focus on what’s important for the thing that you’re doing. Also requires, you know, a lot of work. So that’s kind of, you know, playing catch up for lost time so to speak was another challenge. 

Moving from the humanities to STEM that was interesting. Really kind of required a, really kind of a mentality shift in that you know they’re just very different. There are things like the Digital Humanities which are kind of similar to some of the stuff that you know the quantitative work that I did, but it was really more about, I mean they’re just different. It took a lot of having to go out and learn, just really kind of retrain myself. It was basically like starting from scratch to a certain degree which was not easy but you know we were in school for you know as long as we were learning things is not necessarily a difficult task for grad students. Finding the time can be a little bit more of a challenge. It was one of those just had to buckle down, take things slow, know you don’t know everything then just kind of work your way up a little bit. So yeah not easy, but you know I feel like it’s been worth it. 

DEVINE: So you faced challenges with the age relation, going from teaching younger students to having to work for younger coworkers and then this challenge of not having the same educational background as many of your coworkers and then kind of the general challenge of transitioning from working in the humanities, which comes with one mode of research and kind of type of reasoning to a different type of reasoning and use of that reasoning within STEM and different from being at a graduate school to being at workplace that is not a school is also a challenge that you faced. With all of these challenges that you’ve overcome, what would you recommend to current graduate students interested in pursuing a career in the private sector?

SCHWEIGERT: One, you know, if it’s something you wanna do or you decide that it’s time to make that choice like get started soon. Sometimes I kick myself for waiting as long as I did but you know I’m happy I dropped out it. It made sense for me. If it’s something you want to do, you know, don’t feel bad about it. Nobody cares that you didn’t finish. So that’s one thing I would say. Don’t be afraid if you decide that you don’t want to keep going down that route that you’re on. Definitely don’t be afraid. The other kind of guess more practical advice that if you’re looking to get into the private sector, I can speak more for the programming and development side, but I think this probably applies more generally one of good things to do at first is you know even before you’re ready to start applying for jobs is just look at what postings are out there and what skills are in demand. You know, a lot of times people are trying to hire specific skill sets. If you look at, you know, twenty or thirty or fifty or sixty of these postings you begin to see some trends, see kind of what’s hot, if you’re trying to learn a new skill or pick something up this can kind of key you into what’s hot on the market which I think is just, you know, good advice. 

The other thing particularly, for someone who’s kind of transitioning from something academic to something more industry or private sector focused is look at ways you can kind of start to either network or build some kind of eminence, you know, writing blog posts if there’s a topic, if you’re super into like building like, you know, running technology at all. You like raspberry pies like building stuff like that, start a blog and write about it. Showing that you started like I wanna learn how to be like a network administrator. Start a blog and write about the things that you’re learning. One it shows commitment to you know you probably been writing for a while so you’re probably pretty good at it. Three it’s something you can point to on either a resume or a job application. Like you know I’ve done some things in this sense. That you’re not just like this blank slate you know walking in. You have some kind of knowledge or can show some kind knowledge about something. Similarly like if software development, open source, tons of projects out there on Github and Gitlab and other places that are looking for people to come in and contribute part time, you know, an open source contribution or two on your resume people love it. Its public work. You get to work with great developers. So that’s, you know, another thing you can look at is getting involved in open source. Kind of even as you know part time, a little bit of work here, you know, it begins to show that you can write code, that you can develop, that you can work with people, that you can release things. Thirdly, like local meetups or that kind of thing, you know, meet people in person like if you’re interested in, you know, technology. Find some technology meetups. Go meet people. Network. That’s often a way to kind of find jobs as well.

The third recommendation is one that I hate to give but you kind of have to, is that if you wanna get into software development at all start with as they say grinding wheat code. Algorithm tests, these online algorithm tests at a place like Wheat Code and Hacker Rank, you just got to start drilling them. Most of the applications these days will involve some sort of coding interview where you have like thirty, forty-five minutes to write some algorithm. There’s a bunch of websites online that have practice problems but you basically just kind of have to drill it which can be a job in and of itself. Yeah, if you want to get into software development that’s, start learning your algorithm, start learning your data structures, start practicing them, would be fairly important. 

DEVINE: Well that all sounds like really great advice. And I just want to thank you so much for joining us on Alumni Aloud. Any final word?

SCHWEIGERT: Thanks for having me. You know, it’s been interesting went back and listened a few of these before it’s kind of interesting to hear everyone’s stories, you know, the different paths that people have taken. So yeah thanks for having me. 

DEVINE: Thank you for joining us. 

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