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
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
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
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.
• 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 |