Unexpected Interview Qs for Data Scientists
Rising demand for data scientists has forced employers to spend a lot of time weeding out candidates who aren’t really qualified to crunch and analyze information. In the words of Adam Flugel, a data scientist recruiter with search firm Burtch Works in Evanston, Ill., many candidates are “good at talking the talk and putting the right keywords on their resume,” even if they lack the skills and experience necessary to make themselves truly useful to the organization. As a result, recruiters and hiring managers are focusing more on teasing out not only whether the candidate understands the theories and tools behind data science, but whether they can make use of those skills in ways that align with the business, its pressures and available resources. For example, Flugel added, managers have placed greater emphasis on having candidates work through problems, either during an interview or via a take-home test. In order to evaluate strategic thinking skills, the employer might even provide a dataset without any additional explanation, requiring the candidate to discover and report back on its characteristics and quirks. “These questions give employers a sense of whether or not the candidate can actually do the job,” Flugel said. “With a lot of people trying to flood into the market, these are a safe way of making sure the person can really do the work.”
Part of the Business But “doing the work” is often about more than “pure” data science, points out Kathleen Brunner, president and CEO of the consulting firm Acumen Analytics in Plymouth Meeting, Pa. While analytics form an important component of running a business, its processes must be handled in a cost-effective manner. With that in mind, managers will often ask questions designed to reveal the candidates’ aptitude for responsible resource management. For example, Brunner might probe whether candidates understand the importance of providing the right data to the right person at the right time. “This is about applying data science in a business situation, using appropriate time and resources for the problem,” she said.
Surprises in Plain Sight Basic topics—such as communications skills, or the candidate’s passions—often have the biggest potential to catch candidates off-guard. “A lot of hiring managers may ask about things outside of work,” Flugel said, adding that job seekers are often surprised by such questions. “They’ll want to know about your passion projects in data science. They want to see that you’re interested beyond working hours.” Communications and “soft skills” are likewise vital, said Fangzhou Cheng, a master’s degree candidate in Management Information Systems at New York University. Having gone through numerous interviews with banks, consulting firms, insurance companies, marketing organizations and technology firms, she’s arrived at the conclusion that hiring managers want candidates who can put complex concepts into plain language that corporate management can understand. In addition, she observed, your communications skills help employers fully comprehend your level of technical expertise: “By your discussion, they can gauge your experience.” Cheng, who expects to graduate in January 2016, already has a job offer from a startup data platform provider. Her advice to candidates: “I’m not from a statistics background, so my strategy is to show passion. I’d suggest linking your background to data science. Study the job description, find the connection, and show how your skills are transferable.”