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From Academia to Industry, Reflections on a Career in Data Science
1.
2. From academia to industry,
reflections on a career in data science
Juuso Parkkinen, PhD - @ouzor
Senior Data Scientist, Nightingale Health - @NgaleHealth
HICT S5, Aalto University, April 25, 2019
5. The Data Science Venn Diagram
http://drewconway.com/zia/2013/3/26/the-data-science-venn-diagram
6. My career from Academia to ”Industry”
MSc in bioinformation technology
(HUT / Aalto)
PhD in bioinformatics and machine
learning (Aalto)
Data Scientist (consultant) at Reaktor
Data Scientist at Nightingale Health
7. Data Science research: probabilistic
models for biomedical problems
7
More on my research and other projects:
https://ouzor.github.io/projects.html
8. Data Science as a hobby: open tools for open data
Blogging
Open source programming
Open Knowledge -community
Blogs: https://louhos.github.io/, https://ouzor.github.io/
9. Open Data Science at Reaktor
Kannattaakokauppa.fi by Reaktor: http://kannattaakokauppa.fi
More about the model: https://ouzor.github.io/blog/2016/03/08/apartment-price-model.html
10. Nightingale Health
• Biotech company empowering research, healthcare and industry
with molecular health data
• Creates pioneering products to solve the global burden of chronic
diseases, such as cardiovascular disease and diabetes
• Spearhead innovation is the NMR-based technology to analyze
over 200 blood biomarkers from a single sample, with
unprecedented price and quality level
• Built upon an unrivalled scientific foundation with over
200 peer-reviewed publications
11. Problem with chronic diseases:
We are diagnosted, and we are told “yes”, or “no”.
Current focus = Sickcare
Solution:
Nightingale has built a blood testing technology
that helps us forecast our health in chronic diseases.
We want to enable preventive & personalized
medicine in global healthcare.
12. Lipoprotein particle size
Glycerides & phospholipids
14 lipoprotein subclasses
Fatty acid saturation
Cholesterol
Apolipoproteins
Fatty acids
Ketone bodies
Inflammation
Fluid balance
Amino acids
Glycolysis-related measures
Multiple
use areas
Research
Cardiovascular disease
Diabetes
Maternal health
Ageing
Healthcare
Screening
Diagnostics
Treatment follow-up
One sample One test Comprehensive
metabolic profile
Nightingale’s technology
13. Data Science at Nightingale Health
Individual markers
Traditional vs. Nightingale risk score
15. Uncertainty and luck
I did not have everything planned beforehand
My career choices may make sense in hindsight,
but there has always been a great deal of
uncertainty involved
I have been lucky to end up where I am
16. Failing and learning
My PhD time felt like a series of failures, but after some time I
have realised how much I can learn from those moments.
Experience also helps to put things in perspective
• Data science is often just a small part of all the technology
used to solve real problems
• Technology is often just s small part of the solution
17. Transition from academia to industry
Why did I do it?
Am I happy with the transition?
How is the work different?
What about work-life balance?
18. Transition from academia to industry
Why did I do it?
Am I happy with the transition?
How is the work different?
What about work-life balance?
There are pros and cons in both –
find the one that suits you best!
21. Scientists and entrepreneurs… go hand in hand!
The key to success in
both is to ask good
questions!
https://twitter.com/rsiilasmaa/status/1078203532661014529
22. Design thinking helps in asking good questions
Read more: Design Thinking for project managers and entrepreneus
https://medium.com/pm-insights/design-thinking-for-pms-and-entrepreneurs-77d4304c2b99
“Engineers and business people are trained to solve
problems.
Designers are trained to discover the real
problems.
A brilliant solution to the wrong problem can be
worse than no solution at all: solve the correct
problem.”
Don Norman in The Design of Everyday Things
23. Life after PhD is uncertain
PhD training mostly prepares you for a
tenure track - yet most of you will not get
a permanent position in academia
You will thus face a lot of uncertainty
about the future
Accept and embrace the uncertainty:
look for new opportunities
24. How do lucky people generate their own fortune?
They are skilled at creating and noticing chance opportunities
They make lucky decisions by listening to their intuition
They create self-fulfilling prophesies via positive expectations
They adopt a resilient attitude that transforms bad luck into good
Richard Wiseman They Luck Factor,
http://www.richardwiseman.com/resources/The_Luck_Factor.pdf
25. Reach out
Make your work visible: Write a blog, code stuff - be creative
Visit events and talk to people, also outside your bubbles
Read books and educate yourself broadly
Doing these things will help you shape your future, be it in academia or industry
28. PhD training makes you good at
Trying, failing, and trying again
Tackling big problems systematically
Accepting ignorance and asking questions
Respecting science and the scientific method
Continuous learning
Communication
29. Learn to do things right
Personal time management
Effective team work
Continuous improvement
Hint: It’s all just common sense!
Links:
How agile project management can work for your research:
https://www.nature.com/articles/d41586-019-01184-9
Boss Level –podcast: http://www.bosslevelpodcast.com/
31. Recap
Seek good questions, not answers
Accept and embrace uncertainty about the future
Reach out to the real world
Recognize things in your PhD training that help in facing uncertainty
Continuously improve the way you work
32. Thank you!
Juuso Parkkinen, PhD - @ouzor
Senior Data Scientist, Nightingale Health - @NgaleHealth
www.nightingalehealth.com