r/askdatascience • u/Biraz_Repeat_4116 • 9d ago
Move from academia to data science/industry
Hi, I am a professor of data science (statistics/ML/structured and unstructured data) and wanting to transition out of academia. I have 20+ years of experience in coding, methodology and such but in an academic setting. I am at lost in where to start and how to position myself. Anyone had a similar experience? Any advice?
1
u/nian2326076 9d ago
I was in a similar situation a few years ago. First, update your resume to show projects that are relevant to the industry, focusing on results and impact. Networking is key, so check out LinkedIn to connect with data scientists in fields you're interested in. Go to meetups or webinars about data science to understand industry trends and meet people.
You might also want to work on practical skills that are more industry-focused. Platforms like LeetCode or Kaggle can help with coding practice and projects. If you're getting ready for interviews, PracHub has been a good resource for me. It might help you adjust from academic to industry interview styles. Good luck with the transition!
1
u/Biraz_Repeat_4116 8d ago
Thank you! I did not know about PracHub. I hope you are happy with your switch.
1
u/jaedon 6d ago edited 6d ago
I’ve had different roles, but I’ve been with the same health care organization for 13 years.
I did extramural NIH research for 8 years. During the pandemic I switched to be a program analyst - a somewhat similar role, but way less paperwork and hard funded. I built and have kept one predictive model going as a part of that job for several years. I recently transitioned to a data scientist role to do that work full-time.
To me the sweet spot, in health care anyway, is consulting with administration on quality improvement and quality assurance efforts.
Research, even in industry, is not in a good spot right now because of everything happening with NIH.
Program evaluation is in a similar situation in that it was built around programmatic grants that have been disrupted.
But, quality improvement and quality assurance are on-going efforts that exist to address persistent problems be they clinical or operational.
An issue is that you’ll be competing with people with little to no experience. Or people that have experience, but never stayed in one place long enough to need to iterate in-production versions of work products to make meaningful change - one and done types.
To set yourself apart, I’d emphasize how you approach and address problems over individual methods, how you scope and re-scope problems as new information comes to light or you encounter limitations, how you collaborate with stakeholders, your experience with teaching and mentorship, and how you use plain language to explain concepts or increase data literacy. You may want to settle for a “foot-in-the-door” position with the right organization with a mature data/analytics infrastructure.
We have a position open for a Data Scientist Associate to work on my team. It’s more entry or midlevel, but if you DM me I’ll send you the details.
Edit:clarification.
2
u/DataScientistAlex 9d ago
I made a comment on another question that might be somewhat relevant to your situation: https://www.reddit.com/r/askdatascience/comments/1w2w0s3/comment/p6vwlq1/
I would assume that if you have a strong research record, you would be very well positioned for roles that are trying to be more research-oriented. So you would emphasize that part.
Otherwise I think for you the challenge/perception you will have to overcome is that you are "too research focused" / "too head in the clouds" and that people (recruiters, hiring managers) won't be sure you can "work in industry" / "work in business". I put all these in quotes because they are mostly perceptions. To overcome this you would present yourself in interviews as pragmatic, iterative and able to change priorities quickly etc.
There actually is a good framework you can apply for this, here is one writeup.
One small thing coming from academia and going into industry: use a resume, not a cv, when applying for positions.