How to get interviews and the employment contract. A roadmap workshop on transitioning to the industry in a #datacareer, e.g. Data Scientist, Data Analyst, ML engineer, NLP practitioner, etc. Benefit from the insights of Europe's leading 1000+ practitioner community, including Ph.D. role models from STEM disciplines and the social sciences that now enjoy a #datacareer.

1. 10,000
Data
Scientists
for Europe
Science to Data Science
PhDs and postdocs moving to startups and industry

2. Ten examples*
Dr. Lisa Heße
Dr. Harald Hentschke
Dr. Macarena Beigier Bompadre
From the MPI Infection Biology to Data Scientist with a
knack for ML solutions
From a PhD in Communications Engineering to
optimization algorithms in Data Science
Dr. Dina Deifallah
Dr. Juanjiangmeng Du
From Postdoc in Genomics to ML expert
From theoretical physics to DL expert for visual search
at scale
Dr. Karthick Perumal
From beamline scientist at DESY to ML engineer in
automotive
Dr. Lorenz Kemper
From PhD in Econometrics to Data Scientist
Elizaveta Fotina
From technical assistant at CERN (M.Sc.) to Data
Analytics consultant
From senior research scientist at a university hospital to
freelance Data Scientist
Dr. Setareh Sadjadi
From a PhD in Chemical Process Engineering to Data
Scientist
Dr. Johannes Mosig
From PhD in Mathematics to ML researcher in
Conversational AI
*from the AI Guild community

3. Free online support for PhDs
Webinar Slideshare
Medium
publication
>5.9k views of Science to
Data Science workshop
presentation slides over the
past 2 years.
You can view the latest slides
here.
Some noteworthy items
§ The Women & Data
Science scholarship with
>3.7k views
§ Moving from science to
data Science in 6 to 9
months with >1.9k views
and 64% read ratio
§ The industry-ready CV or
Résumé with a 68% read
ratio
We offer a free webinar.
Registration is via
datascientist.eventbrite.com
Events are also published on
the Facebook page to which
you can subscribe - and also
support the campaign 10,000
Data Scientists for Europe
with a review.

4. Before investing in further training and upskilling,
take the opportunity to reduce
your cost by 90% and search time by half.
New: Do your CV first
https://www.datacareer.eu/post/do-the-cv-first

5. Awesome CV feedback. I am
applying, and 50% of the
companies invite me for an
interview. Cheers!
I enjoyed working on the CV
and preparing the
interviews. In the end, I had
the luxury to choose
between 2 job offers.
Oliver Kaul
Ana Mikler
Really happy
about the
experience and
the way it is
helping me land
more interviews.
Richa Sharma

6. #datacareer
“No matter who you are, self-improvement is one of
the most important and most overlooked attributes
of young AI talent. It only takes four years of
experience to become a senior, or five years of
experience to lead. The determination and
discipline to improve both the hard and soft skills
continually will be the deciding factor.”
Jean-François Gagné

7. The next 20 years
Starting a
#datacareer
The industry-
ready CV
Roadmap to
getting hired
Outline

8. Dr. Macarena Beigier-Bompadre
Alumna, MPI for Infection Biology
Alexander von Humboldt Foundation
University of Buenos Aires
LinkedIn

9. Dr. Dina Deifallah
PhD in Communications Engineering,
The American University in Cairo
LinkedIn

10. 10
Dr. Chris Armbruster
Alumnus, Max Planck Society (MPDL)
European University Institute
Jean Monnet Fellow
Lancaster University, UK
LinkedIn

11. Starting a
#datacareer
1

12. The fastest growing labor market for the
highly qualified
§ 2020 global labor market
baseline is 500,000 practitioners
§ Numerate PhDs and postdocs
from any discipline are suited
§ Experience with Python, R , and
SQL facilitates smooth transition
§ Increasing specialization for data
roles and domain expertise
§ We have contributed to >200
industry and startup CVs
§ Supported transition right after
the PhD, as well as PhD +1 to +3
years
§ Also successfully handled PhD +7
to +11 years
§ Building the AI Guild platform for
practitioners at datacareer.eu
Key facts Track record

13. When do I switch career?

14. What data role do I seek?
AI Career Pathways: Put Yourself on the Right Track
By WORKERA, a deeplearning.ai company

15. What is the market situation?
JF Gagné: Getting the Needed Talent Along the AI Value Chain
(Data for 2020)

16. How is
the field
evolving?

17. Where to?
CORPORATE STARTUP CONSULTING

18. Roadmap to
getting hired
2

19. #datacareer
exploration
domain
choice
search v
training
#datacareer
start
Overview

20. Test-drive a few online courses or select some relevant
training books.
Find a practitioner in your network to interview.
Talk to recruiters and recruiting firms.
Interview alumni of training providers that have made the
career switch (e.g., online course, bootcamp, university
degree).
Write up your industry-ready CV.
#datacareer exploration

21. Explore and understand the use case & the business case for
data analytics and machine learning.
Identify preferred domains for your career entry, e.g., by type
of data, data role, and approach (tools and methods).
Find out which industry or use case offers the biggest
opportunity (e.g., high demand, low entry barrier).
Apply to a few suitable career openings and put your
industry-ready CV in front of relevant people.
domain choice

22. Be proactive with a search and mission statement (and let
people help you).
Be aware of the trade offs between your preferred
employment versus further training.
If further training is what you want, consider ramping up as
fast as possible (full-time; practitioner-led).
An interesting alternative to training is building a domain
portfolio.
search v training

23. Understand that network contacts, recruiting firms, and
direct applications are equally important to get your CV
placed directly in front of hiring managers.
Practice how coding challenges and personal interviews may
be different and tougher.
Look at salary surveys and define your expectation, e.g., for
Data Science in Berlin €60-70k p.a.
Make sure you have some criteria to evaluate job offers, e.g.,
team, growth opportunity, location, and salary.
#datacareer start

24. The industry-
ready CV
3

25. Information and research
A summary of the key
elements of an industry-ready
CV is available on Medium.
The outline of the AI Guild
#datacareer CV is on the
website.
Please do your own research,
e.g., on Data Science &
Analytics salaries and job
profiles, transferable skills,
online portfolios.

26. The industry-ready CV
Get considered by
highlighting your
technical skills
Be invited for
interview by
demonstrating your
business skills
Lead on the
interview by
telling your data
experience
Focus your search
with a
professional
mission

35. The next 20
years
4

36. The
industry
investment
landscape

37. Startup
market
map

38. Local
players

39. Organizing
AI
at scale

40. 10,000
Data
Scientists
for Europe
Appendix

41. #datacareer cheat sheet
PRACTITIONERS ALUMNI RECRUITERS “BRING A
FRIEND”
Find a 1st or 2nd degree connection
via e.g.
- LinkedIn, Xing or similar
- Academic alumni networks
- Meetup, conference or similar
Find someone who has successfully
changed career via e.g.
- LinkedIn profile (experience or
certificate)
- Course provider evaluation
platforms like Course Report or
Switch Up
Ask your search engine to find e.g.
- Firms recruiting only for data
roles
- Salary surveys for data roles
Many firms recruit also by ‘bring a
friend’.
You can ‘reverse engineer’ the
strategy by asking your 1st degree
connections to look at your CV – and
pass it on at their company
internally if there is a fit.

42. #datacareer cheat sheet
#AIUSECASE BUSINESS CASE DOMAIN CHOICE ACTIVE SEARCH
Start from your experience, e.g.
- Use and compare the AI of
products you already have
- Use or buy more products, e.g.,
voice systems if you are
interested in NLP
Read up on the business case and
connect to use cases e.g.
- Harvard Business Review or
similar type of resource
- Dedicated online tech
publications
- Publications of companies
evaluating the field in a data-
driven manner
Jump start your domain orientation
by e.g.
- Using market maps for fast
orientation
- Identifying your preferred type of
data like text, numbers, images,
speech etc.
Please remember to include a clear
statement on your CV and LinkedIn
profile that says
- When and where you want to
start
- What domain and/or type of
company you would like to be in
- What you have or bring
especially

43. Highlights in 2020
MPI for Radioastronomy, Bonn
“Science to Data Science: PhDs and postdocs moving to
industry and startups”
Zoom event on 24 April with Dr. Chris Armbruster
IMPRS-gBGC and IMPRS-CE, Jena
“From Scientist to Data Scientist”
Zoom workshop on 15 June and 21 August with Dr. Dina
Deifallah, Kirstin Taufertshöfer, and Dr. Chris
Armbruster
Max Delbrück Centrum for Molecular Medicine, Berlin
“Empowering PhDs and postdocs to start a #datacareer in
the industry, startups, and consultancy”
Zoom workshop on 04 December with Dr. Dina
Deifallah, Dr. Macarena Beigier, and Dr. Chris
Armbruster
Max Planck Society Career Steps 2020
“Data roles in industry for PhDs: Is a role as data analyst,
data scientist, or data engineer best for me?”
Cisco WebEx on 15 October with Dr. Lisa Heße, Dr.
Macarena Beigier, and Dr. Chris Armbruster
“From Science to Data Science: PhDs and postdocs moving
to startups and the industry “
Cisco WebEx on 05 November with Dr. Paul Elvers and
Dr. Chris Armbruster
“Leaders reflecting on key trends in data careers and the
application of data analytics and machine learning”
Cisco WebEx on 19 November with Dr. Marija Vlajic
Wheeler, Prof. Dr. Patrick Baier, and Dr. Chris
Armbruster

44. Ask your academic institute
to invite the AI Guild to
deliver a workshop
Your career development office, institute head, or
professor can use these slides to book
https://www.slideshare.net/ChrisArmbruster/ho
w-academic-institutions-best-support-phds-and-
postdocs-in-the-transition-to-a-highly-paid-
datacareer