Benjamin W. Campbell received his Ph.D. from The Ohio State University’s Department of Political Science in 2019, where he is a visiting fellow. He is currently a data scientist at CoverMyMeds, a healthcare software company based in Columbus, Ohio. He maintains an active research agenda centered around the development and application of network inference methodology.
What kind of work do you do at CoverMyMeds? What energizes you about your career?
At CoverMyMeds, our mission is to help patients get the medication they need to live healthy lives.
One way we do this is by simplifying a process called Prior Authorization, whereby doctors lobby a patient’s health insurance on their behalf to cover a certain medication. As a Data Scientist, I develop data products that are designed to help patients get on medication faster than they otherwise would. One product I am currently developing will tell us when Prior Authorizations are likely to be unsuccessful, and when switching to different medications could get patients on therapy much faster.
I wake up everyday excited to go to work because I get to work with so many brilliant, wonderful people tackling a problem that everyone has, or at some point will likely encounter. Often times when I was a grad student I struggled to see how my work might directly improve the lives of others. It’s nice to go to work never having to worry about that.The work I am most proud of, however, is the work that I’ve done in substance use disorder recovery. At Ohio State, I was fortunate to have the opportunity to use my skillset in network analysis to understand how an individual’s social network can be used as an effective treatment in promoting recovery.
What did you study in graduate school? Can you say a little bit about your research?
In graduate school, I studied a little bit of everything! Most of my work was centered on refining the tools we use to study political and social phenomena. I was particularly interested in network analysis, and how we can model the heterogeneous motives that actors have for forming social relations.
My dissertation examined the capability aggregation model used to explain military alliances, arguing instead that countries use alliances as institutions to fulfill a variety of different objectives. To measure these heterogeneous interests, I developed a model-based clustering algorithm that allows users to detect patterns in how actors structure their networks.
The work I am most proud of, however, is the work that I’ve done in substance use disorder recovery. At Ohio State, I was fortunate to have the opportunity to use my skillset in network analysis to understand how an individual’s social network can be used as an effective treatment in promoting recovery.
Why and when did you choose to pursue a career in tech?
Tracing exactly why I made the decision is kind of difficult. I don’t think it was really one thing, but a confluence of things.
I was on the academic market, had a handful of fly-outs, and unfortunately nothing went my way. I could have given the market another year, but honestly, I was exhausted and my mental health was struggling. The academic job market was one of the hardest things I had ever done, and I didn’t know if I had one more year of it in me. Then it hit me, it likely wouldn’t just be one more year. Even if I got a job, who is to say that I wouldn’t be on the market again at some point. The process also made me realize that as someone who very much enjoyed the diverse and interdisciplinary nature of my work, there would be few academic departments that I would truly feel at home in.
Around that time I had two different conversations. The first was with my now-fiancé, who asked me whether I would like to live wherever I wanted and do something else, or move somewhere that someone else told me to so that I didn’t have to change my career. I found myself favoring the former over the latter. The second was over a cup of coffee with a mentor who had been tasked with the same choice I had, and for which things had turned out very well once they’d chosen a career in tech. He gave me a sense that I’d likely thrive in a data science position. Interestingly enough, on my drive home from that cup of coffee, I got a call from my last fly-out telling me that I hadn’t gotten the job. I think it was then that I made the decision that I wanted to pursue a career in data science.Everyone remembers just how hard of a decision it is, and just how much anxiety there is about changing careers. There’s no need to go through it alone, there’s no need to reinvent the wheel. People can help.
In what ways did your doctoral training help you in your career?
In what ways didn’t it! It’s jarring just how similar my day-to-day now is to how it was when I was a graduate student. Yeah, I have a lot more meetings now and find myself doing more administrative work. Instead of overseeing data collection efforts, now I query data from our databases. Instead of writing up results in a manuscript, I present some reports and deploy APIs. But, the majority of my time is spent doing the same sort of data work I did as a graduate student. All of the project management, data tidying, data exploration, and predictive modeling work I did as a graduate student I do now as a data scientist.
When you’re going through a doctoral program, I don’t think you realize just how much the skills you’re picking up travel across domains. In fact, I think one of the hardest parts is figuring out what skills you have already picked up that others find valuable.
Do you have any advice for PhD students considering a career in tech?
If someone from your program has pursued a career in tech, talk to them. If you’d be the first, reach out to me, or any of the other folks who have done it. Everyone remembers just how hard of a decision it is, and just how much anxiety there is about changing careers. There’s no need to go through it alone, there’s no need to reinvent the wheel. People can help.
There are plenty of different roles that graduate school could prepare you for. There’s more than data science out there, so it may not make sense to take all the statistics and programming classes you can if they’re not of interest to you. For example, if you are more interested in psychology and experimental design, some data science or marketing analytics positions may be of interest, but you might also be interested in user experience (UX) research. It’s important to have those conversations with alumni who can help you find a role that you might love!
APSA’s Career Paths series explores the wide range of career trajectories that political science PhDs can take and provides specific career advice for graduate students entering the job market, as well as other political scientists at all career levels who are looking for new career opportunities. Individuals interested in contributing to the series should email Dr. Tanya Schwarz, APSA’s Director of Teaching & Learning, firstname.lastname@example.org.