I’m currently on leave to do an internship at a startup company. When people asked me why I decided to pursue an internship, I replied (in jest) that after so many years of grad school, I should try to show that I’m still employable. Today I read an article that suggests this is more true than I realized.
The article by Chand John, a PhD grad in Computer Science from Stanford, underscores the importance of industry experience or exposure when targeting an industry job after graduation. John’s job search (thankfully successful) took one whole year. He went to informational interviews, he vetted his resume with friends in industry, he studiously prepared for each one-on-one interview. Getting interviews? Not a problem, he landed more than 30 interviews before finding a job which interested him and a company willing to take a chance on a PhD grad with no industry experience:
No one could pinpoint anything I was doing wrong. Professors and industry veterans inferred I must be saying something really crazy to destroy myself in 30-plus interviews: There was “no way” a person with my credentials could be denied so many jobs. However, I had said nothing crazy. My interviews had largely gone smoothly. And I did eventually land a job closely related to my Ph.D. But the opportunity didn’t arise until a year after finishing my doctorate. Before that lucky break, my accomplishments and efforts weren’t paying off.
As a scientist, I had already been gathering data about that question. Each time I was rejected from a job, I asked the companies for reasons. They were often vague, but two patterns emerged: (1) Companies hesitated to hire a Ph.D. with no industry experience (no big surprise) even if they had selected you for an interview and you did well (surprise!). And (2) my Ph.D. background, while impressive, just didn’t fit the profile of a data scientist (whose background is usually in machine learning or statistics), a product manager (Ph.D.’s couldn’t even apply for Google’s Associate Product Manager Program until recently), or a programmer (my experience writing code at a university, even on a product with 47,000 unique downloads, didn’t count as coding “experience”).
On the first reading, this article struck me as quite sombre: if this Stanford PhD grad took a year to find a job, what hope do the rest of us have? But after reading more carefully, I noticed there were some important steps he did not undertake which put him at comparative disadvantage: the lack of industry experience, the mismatches between his skills and the skills that employers were looking for (viz: machine learning experience for data science jobs). So what does this mean for PhD students looking towards industry after graduation? Don’t just assume your status as a PhD grad will make you an attractive candidate. PhD students don’t have a monopoly on learning quickly. When competing for industry jobs, assume you’re only as attractive as your skills, your experience, and your portfolio.
If we want to transition into industry after graduation, then we need to make ourselves into attractive candidates for those jobs. That could include internship experience to develop your portfolio. That could mean contributing to OSS projects that have credibility in industry. That could mean taking the classes which may not directly relate to your current topic, but will help you develop skills which are in demand.
John closes with a salient point: public dollars funds much of PhD research. The government investments in students to develop their skills, and in exchange these grads will repay this investment many-fold over their careers, enriching society with the output of their work. When PhD grads struggle to contribute, everyone loses.