Exploring the Realities of a Mathematics Career in Industry

By Lina Sorg

Rapid growth and development in the fields of data science, machine learning, and artificial intelligence are shaping the nature of industry-based research. The continued evolution of these areas offers increased employment opportunities for applied mathematicians and computer scientists in business, industry, and government (BIG) settings. A virtual panel discussion at the Second Joint SIAM/CAIMS Annual Meeting, which took place this July, explored the nuances and expectations of work beyond the realm of academia. Panelists consisted of Christiana Manzocco (Analythium.io and Alberta Enterprise Corporation), Nandi Leslie (Raytheon Technologies), Vakhtang Putkaradze (ATCO Ltd.), Sumanth Swaminathan (Vironix Health), and Stefan Wild (Argonne National Laboratory). They engaged in a lively conversation about their varied experiences in industry and offered advice for students and early-career mathematicians in search of BIG employment. The panel, chaired by Kevin Bongiovanni (Raytheon), was followed by an online mixer where attendees could network and engage with the speakers.

Students at both the undergraduate and graduate level often inquire about the coursework and skill sets that make them desirable employees. Putkaradze emphasized that there is no “correct” educational path. “What we’re looking for in reality is an agile mind and someone who can learn new things easily,” he said. “There’s a push for people to learn machine learning and data science. But what we need to understand is that those are tools, not a magic wand for solving every problem.” Students should possess a working knowledge of foundational subjects and a deeper, more thorough grasp of technical material—especially in their areas of expertise—that extends beyond the simple use of a formula to solve a problem.

While many companies generally try to avoid constraining their hiring prospects based on specific tools, the panelists acknowledged that candidates should be able to quickly familiarize themselves with any necessary programs or languages. Swaminathan also suggested that substantial experience in a language other than MATLAB is valuable, while Wild recommended that all recent graduates be comfortable with version control and use it to maintain their CVs and personal websites.

During an interview, successful applicants demonstrate a clear understanding of the technical area in which they will potentially be working. “It’s really critical to feel confident in the company you’re going to interview with, and confident in your knowledge of what you’re doing,” Leslie said. “Really know your own portfolio and how you fit into the company.” This level of preparation involves researching a company’s vision and objectives beforehand, and catering interview preparation to each specific role.

The panelists agreed that mathematicians, engineers, and physicists are some of the best thinkers in the world, which helps them stand out in a competitive market. “The advantage of having an applied math background is that if you have a flexible and agile mind, you can learn quickly and know all kinds of things,” Putkaradze said. “We focus on the depth of studies, but in industry your knowledge cannot be like a delta function and very narrow; it should be more like a pyramid.”

Clockwise from top left: Kevin Bongiovanni (Raytheon Tecnologies), Vakhtang Putkaradze (ATCO Ltd.), Sumanth Swaminathan (Vironix Health), Nandi Leslie (Raytheon), Stefan Wild (Argonne National Laboratory), and Christiana Manzocco (Analythium.io and Alberta Enterprise Corporation) participate in a virtual panel discussion about mathematics careers in industry at the Second Joint SIAM/CAIMS Annual Meeting, which took place in July.

Maintaining a wide variety of interests is also beneficial. Swaminathan spoke about his own interdisciplinary interests, which extend beyond the fields of science, technology, engineering, and mathematics (STEM). These passions inspired multiple skill sets that proved useful in the industry sector, though he did not exercise them much as a postdoctoral researcher. As a result, Swaminathan looks for candidates who demonstrate the aptitude for collateral thought and hires critical, hypothesis-oriented thinkers.

BIG organizations are especially partial to these types of well-rounded candidates because industry mathematicians often work within multidisciplinary teams. “We greatly value the ability to collaborate with diverse colleagues, in terms of background and technical expertise,” Wild said. Manzocco, who has a background in management and consulting, echoed this sentiment. She added that collaboration between people with varied proficiencies is often necessary to obtain results. “Most corporations are still completely clueless about how to derive any value from their data,” Manzocco said. “It’s a big, dirty secret that no one wants to talk about.” Because the data is often disorganized and spread between different functional teams and departments, employees with starkly different backgrounds—both inside and outside STEM fields—frequently work together to transform the data and extract business value.

As a strategic advisor at Analythium, Manzocco is involved in many simultaneous projects and spends her days talking to clients, recognizing their problems, and scoping their needs. After identifying and understanding an issue, she brings it back to her team and liaises with software programmers and developers to create a dashboard for the client. Strong communication and problem-solving abilities are thus particularly important in this type of interactive role.

Conversation then turned to the significance of mentorship, which frequently leads to networking prospects and rich collaborations. “I believe mentorship is critical at all stages of your career,” Manzocco said. “As a professional, there’s an opportunity for you to receive and give mentorship all along that continuum.” She reminded attendees that there is always more to learn, regardless of one’s experience level. The most effective steps when building a network include getting to know people, asking for and seeking out introductions, and learning about other individuals’ work. Manzocco has never once applied for a role through a job board; all of her positions have resulted from networked connections.

Wild mentioned that now is a good time to make some contacts at the national laboratories since most labs currently have available positions. Leslie offered several possible leads for students and postdoctoral researchers. The National Research Council (NRC) and the National Academy of Sciences have openings for students at all levels, and the NRC Research Associateship Programs offer different tiers of funding and periods of performance, depending on one’s education level and application strength. Oak Ridge Associated Universities also provides fellowships that place successful applicants at a laboratory where they can find advisors and mentors.

The technical and computational work at these labs—and elsewhere in industry—goes well beyond machine learning and data science. “There’s lots of traditional math that you can use in different circumstances,” Swaminathan said. “It’s not a fully data-science-monopolized industry. In early industrial mathematics, I was doing a lot of work to solve traditional transport problems.” Tackling these problems helped to expedite product development.

Leslie has also worked outside the machine learning domain. She has utilized game theory, stochastic processes, and probability theory in recent years, and indicated that industry mathematicians often apply optimization methods and other mathematical approaches that stem from operations research.

The speakers spent the last few moments of the panel discussing the realities of work-life balance, which depends on the nature of the organization in question and the structure of one’s job. “My first few roles were really a grind,” Manzocco said. “I put in a lot of time and long hours. But as I navigated my career, I was able to carve out positions that were a little better for me.” She praised her employers for being fairly flexible with schedules. Swaminathan, who has spent the last five years in start-up culture, is also satisfied with the flexibility he has experienced. He works all the time, but that is solely by choice. “Some of this is on you, some of it is on the company,” he said. In many cases, industry positions are much more accommodating than academic appointments.

Ultimately, the panelists encouraged attendees to continually expand their interests, actively seek out opportunities, take initiative, and prioritize experiences and interactions over the rigidity of learned coursework. “The courses you take are probably obsolete by the time you finish the final,” Putkaradze said. “Don’t take courses or degrees as something that will be the end of your education. They’re just the beginning.”

Lina Sorg is the managing editor of SIAM News.