AN22 Panelists Discuss Career Opportunities in Business, Industry, and Government

By Lina Sorg

The rapidly changing nature of research and development continues to introduce a wide variety of new career opportunities beyond the realm of academia for applied mathematicians and computational scientists. During a hybrid session at the 2022 SIAM Annual Meeting, which took place in Pittsburgh, Pa., this July, six panelists shared their real-world experiences in business, industry, and government (BIG) with a rapt audience of students and early-career professionals. Sharon Arroyo (The Boeing Company), Marisabel Rodriguez Messan (U.S. Food and Drug Administration), Helen Moore (University of Florida), Ian Price (UPMC Health Plan), Juliana Richardson (MITRE Corporation), and Pablo Seleson (Oak Ridge National Laboratory) offered personal anecdotes and advice for embarking on a successful career in BIG. Kevin Bongiovanni (Raytheon Technologies) and Nessy Tania (Pfizer Inc.) moderated the hour-long panel.

Arroyo opened the session by admitting that she did not even consider a career in industry while pursuing her Ph.D. in operations research. Upon earning her degree, she secured an assistant professor role at Iowa State University that involved collaboration with industry groups. Arroyo quickly realized that she thoroughly enjoyed the interdisciplinary nature of these problems. “I really liked seeing what the math did, how it impacted industry, and the value that it had for the company,” she said. After three years, she left Iowa and joined the Applied Mathematics Group at Boeing; Arroyo has remained with Boeing for 26 years and is now a Senior Technical Fellow.

 Like Arroyo, Moore never initially intended to pursue employment in industry. Yet after collaborating with a medical group on leukemia research that corresponded with her academic work, she applied for a position at a biotechnology company called Genentech. Moore quickly received an offer and subsequently spent the next 15 years at various companies, including Bristol Myers Squibb and AstraZeneca. “Not only is the mathematics incredibly beautiful, but it can also help people who are very sick,” Moore said. “That really drives me.” She currently runs a mathematics research group within the Laboratory for Systems Medicine at the University of Florida; similar research groups exist at the University of North Carolina, University of Texas, Houston Methodist, and Moffitt Cancer Center. Moore reminded attendees that such programs—which employ mathematicians but are located outside of academic math departments—present rich opportunities for partnerships with scientists who are working on data-driven projects that have mathematical components.

After earning her Ph.D., Rodriguez Messan spent several years in academia before accepting a job with the U.S. Food and Drug Administration (FDA). She was impressed by the agency’s research efforts, which include applications to cancer and immunotherapy, and liked that the position allowed her to utilize many of the skills that she acquired in graduate school. Rodriguez Messan has now been with the FDA for nearly three years and enjoys her team’s analytical focus. “So far it’s been a really nice experience,” she said. “I’ve started learning more about different subjects, the problems are challenging, and I find myself learning new mathematical skills and new ways to apply those skills to modeling.”

Unlike his counterparts, Price never considered a career in academia and instead went straight into industry. “I really wanted to make an impact, get my hands dirty, get involved, and see a little more immediacy to my work,” he said. “One of the things I’ve enjoyed about industry is being a bit of a universal hex wrench.” As a lead data scientist at UPMC Health Plan, Price aims to provide stakeholders and customers with what they need, rather than a hypothetical version of what they think they might need. Yet despite his title, he still considers himself a mathematician; in fact, Price believes that his mathematics background makes him an even better data scientist. For example, the concepts from his graduate-level numerical methods classes help him see things like the impact of convergence in ways that his colleagues might not.

As a research scientist in Oak Ridge National Laboratory’s (ORNL) Computer Science and Mathematics Division, Seleson encouraged attendees to pursue internships outside of academia and explore places like the national laboratories. “It’s very exciting to be in an environment that leads in several areas,” he said, noting ORNL’s focus on supercomputing and operation of Frontier — the world’s first exascale supercomputer. “Over the years, I’ve been engaging with the applied mathematical community on one side and the computational science community on the other side.”

Next, the moderators migrated the discussion to the types of skills that are necessary for success in industry-based professions. Moore emphasized the importance of persuasive communication—both written and verbal—in non-academic settings, as industry employees often report to people who are not experts in their particular areas of specialization. She noted that teaching can be an effective means of preparation for this broader style of communication.

Rodriguez Messan seconded the benefit of strong communication, then confessed that she wished she had become more acquainted with data analysis while in graduate school. Given the growing prevalence of big data, she advised students to take on a data-based project or enroll in a class that involves significant data use. Moore echoed these comments, adding that knowledge of statistics, uncertainty quantification, and sensitivity analysis is also valuable. Furthermore, it is important to keep up with the latest developments in one’s research area — especially in fields like biology or medicine that often progress quickly and in real time. “I get my domain knowledge as needed but am always working to improve my mathematics,” Moore said.

When the moderators opened the floor to questions, an attendee asked about the level of collaboration that occurs outside of academia. In response, Seleson commented on the cooperative nature of national laboratories. “National labs are environments where collaboration is extremely encouraged,” he said. “It’s not always necessary, but it’s very helpful.” Though Price clarified that that the level of collaboration within organizations depends on company culture, he urged all young professionals to develop good networking skills and be present around their colleagues.

Richardson then spoke about her own experiences as a data scientist at MITRE. “I collaborate with people all the time,” she said. “I couldn’t do my job without other people.” Richardson works on several problems simultaneously and thus routinely partners with computer scientists, aerospace engineers, mathematicians, physicists, and other professionals. Because multiple employees often contribute to different parts of a project’s pipeline, they must all communicate throughout the process and understand each other’s roles.

Another attendee inquired about the transition from academia to industry and vice versa. Moore remarked that if she had known she would eventually migrate to industry, she would have made a concerted effort to publish in industry journals, attend industry-based conferences, and otherwise get involved in some capacity. She added that a successful transition depends in part on publishing in applicable journals, encountering the right people, attending and presenting at the appropriate conferences, and networking whenever possible.

In addition, Moore encouraged industry employees to maintain some type of tie to academia, perhaps by giving talks or presenting posters at meetings. “If you at least present a poster, that gives you something from an industry job that you can present during an interview or list on a resume,” she said. Arroyo expanded upon Moore’s comments and urged students who are considering BIG careers to complete an internship with a company so that future employers have tangible evidence of their experience and enthusiasm. In contrast, individuals in academia with an interest in industry might consider consulting as a side business.

Conversation then turned to the nuances of the interview process. One student asked about the types of skills that researchers can bring to mathematics-based industry roles, especially if they have a degree in engineering or another tangential field. Moore advised interviewees to emphasize undertakings with a clear impact. Because industry employers focus heavily on impact, discussing one’s involvement in the application and success of a specific project is thus particularly valuable. For example, candidates can explain their data analysis efforts, the application of a code that they wrote, or their role in the implementation of a new system. 

Moreover, Richardson acknowledged the importance of interviewing with the right people. “Try to target your job search to places where you’ll interact with other Ph.D.s — people with backgrounds in electrical engineering or computer science,” she said. “They’ll understand that [your experience] is relevant and you won’t have to convince them.”

Seleson noted that national labs offer many exciting internship opportunities. “Look into labs, try to find people who work on projects that you may be interested in, and attempt to contact those people,” he said. He also recommended the U.S. National Science Foundation’s Mathematical Sciences Graduate Internship Program: a 10-week session that provides hands-on experience for mathematical sciences graduate students at federal national laboratories and research facilities. In addition, many job and internship openings are advertised on SIAM’s Career Center and sites like LinkedIn, Twitter, and Indeed.

As the session concluded and attendees prepared for the post-panel networking reception, Arroyo shared a few final thoughts about internships. She specifically mentioned that companies post a lot of internships in the fall, which is a good time to start looking for openings for the following summer. “Don’t only search for ‘math,’” she said. “The math could be hidden in other areas. Look under ‘data science’ and ‘data analytics’ as well.”

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SIAM is always interested in hearing more about the needs of our members who work in industry, or who might be considering a future career path in industry. Send your suggestions and questions to [email protected].

Lina Sorg is the managing editor of SIAM News.