Neuromag July 2018 - Page 25

From science to data science: How do I best move to industry as a PhD or Postdoc? Written by Chris Armbruster I have accompanied quite a few PhD students and postdocs in the transition to a job in industry. Even at a later stage – that is a PhD of 5 years and more – this career change is typically manageable in a few months. Demand for new talent in the fields of data science and artificial intelligence (AI) is increasing, particularly also for highly numerate PhD students with experience in handling numbers, images, text, and speech; and prior experience in using Python, R, and/or SQL. When interviewing candidates for a transition to data science, my top three concerns are: 1) A background check for cognitive ability and experience in handling data, 2) The motivation for a move to data science or AI, and 3) A sense of direction or destination in making that move. Which field or in- dustry do you want to join? In managing your transition, prior cod- ing experience in Python or R is very helpful but not essential, as it can be acquired rapidly with a combination of books, online learning and immersive coding experiences. In empowering PhD students and postdocs to move to data science and AI, I would like to do the following: 1) Share some results from an infor- mation campaign that I have been roll- ing out for PhD students and postdocs across Germany. 2) Discuss some pros and cons of con- tinuing in academia or moving to in- dustry as they have emerged from the workshops I’ve held to date. 3) Address the gap between science and data science and how you might close the gap so that a hiring manager will see you as ‘production-ready’, e.g. able to improve and deploy predictive models. 4) Look at how drafting an industry- relevant CV might accelerate your transition, which, once you start, should take you 6 to 9 months. 10,000 Data Scientists for Europe is a PhD information campaign that I have taken to Göttingen, B onn, Köln, Tübin- gen, Stuttgart, Heidelberg, Freiburg, and Karlsruhe, as well as running mul- tiple smaller workshops in Berlin. The 12 workshops have had 576 regis- tered participants and I have collected feedback from 236 attendees. Some results: • The largest workshops were Heidel- berg (109), Bonn (98), as well Tübin- gen and Göttingen (76). • More than 60% of the respondents think a career change to data science very likely, and more than a quarter are definite about the change. • More than 60% want to transition within 12 months or less. • More than 80% have prior coding ex- perience with Python or R. • 4 out of 10 can imagine being a co- founder of an AI-driven startup. At the workshop, I ask participants to discuss the meaning of continuing along the academic track or changing July 2018| NEUROMAG | 25