Start-up opportunities in computational and data science

April 14, 2014
panelists Ian Stokes-Rees, Alex Wissner-Gross, and Amy Zhang

Panelists discuss challenges and rewards of entrepreneurship 

by Anita Mehrotra

Friday, April 4, may have been cold in Cambridge, but the discussion in Northwest Room 169 was animated and lively that afternoon. The topic was the role of data science in start-ups, and the possibilities – and challenges – that come with a career in the world of data science entrepreneurship.

The panelists included academics and innovators from a wide range of backgrounds. Dr. Daniel Weinstock, Assistant Director of Graduate Studies in Computational Science and Engineering, moderated a discussion with three individuals whose wide range of experiences led them to the start-up community. They included Dr. Ian Stokes-Rees, a computational scientist at Continuum Analytics whose background in academia both as a student (Oxford Ph.D., Computational Physics ‘06) and as a research assistant at Harvard Medical School informed his decisions to move into the start-up world; Dr. Alexander Wissner-Gross, a graduate of MIT (S.B. ‘03) and Harvard (Ph.D., Physics ‘08), who identifies as a “serial entrepreneur” and most recently founded Gemedy, Inc, an intelligent systems enterprise; and Amy Zhang, a graduate of Rutgers (B.S. ‘11) and Cambridge University (M.Phil. Computer Science, ‘12), who worked at a news aggregation start-up in New York City before beginning her Ph.D. in computer science this fall at MIT.

Unlike a typical “nine-to-five” job, a career in the start-up world often constitutes working “long hours,” Zhang pointed out. She emphasized that the work-life balance can be vastly different depending on the types of people you work with and their “attitude towards extra-curriculars.”

Though a start-up can be “a totally insane place to work,” Stokes-Rees confided, there are huge benefits to working on problems in a new and innovative way. Start-ups, he claimed, “are where you get to work on the best, most exciting work. [In many ways], it is similar to working in one of the very well-run labs in academia, though the motivators and challengers can be quite different.” And although there is great demand for data scientists at large technical firms like Google, Facebook and LinkedIn, which can offer a more consistent lifestyle, start-ups provide an opportunity to be more autonomous and to “determine what direction the company will go in,” Zhang noted.

The panelists highlighted the fact that a successful career in the start-up world is often completely independent of the type of path taken. In his experiences from four different start-ups, Wissner-Gross found that “[p]eople from all fields thrive.” He went on to note that individuals interested in the start-up world do not need to go through any intermediate phases to jump into the space. “Just go straight to it,” he stressed. “And [above all] never let anyone tell you that you have to choose: you can do both start-ups and academia if you have the will and drive to.”

So what points should aspiring entrepreneurs and start-up employees keep in mind if they are curious to venture into the data science start-up space? All three panelists agreed that outside of essential technical and scientific skills, individuals who succeed in the data science world are those with the right interpersonal skills and a keen ability to communicate. Such soft skills ensure personal and career growth within an enterprise, and are ultimately necessary in order to manage others.

Start-ups are risky places to be at and thus are not for the faint-of-heart or risk-adverse. In fact, most start-ups fail, and several suffer early deaths at the hands of funding problems, board mismanagement, or non-engineered talent acquisitions. As a result, the biggest, yet perhaps most difficult, skill that a future founder or start-up employee must have is to remember that “at the end of the day, you have put in your best and are happy with what you have accomplished… and with yourself,” said Wissner-Gross.