Related Posts
More Posts
History of BCG layoffs anyone?
Currently recruitment in Bangalore for developer
Thoughts on airline stocks? Good time to get in?
God help us. $8 trillion since 2020.

Hi all, Recently i interviewed at Adobe for the post of computer scientist, Noida location. Had 5 technical rounds, but after that i didnt get any further response. One of HR called me and asked me to wait for a day or 2 last week, she gave me the reason that there are some issues going on in company. It's been 2 weeks now and i haven't got any response from them, i have been following up on mail and call, but there is no response either. What could be the reason ?? Any adobe folk out there ??
Looking for a position in Las vegas !?
Additional Posts in Pittsburgh
Hope everyone has a fun and safe Halloweekend!
New to Fishbowl?
unlock all discussions on Fishbowl.




Bowl Leader
As a Data Scientist, I work with these models, but not to the extent of engineering them from scratch or writing them in a language used in production. My background is not in computer science, but I'm very much exposed to software/hardware development, so take my advice for whatever it's worth.
Note: My academic background is in life sciences and a scratch of business. Nearly everything I do in my 9-5 today has no founding in what I learned in school WRT software development. However, WRT data science I am heavy in mathematics/statistics.
If you wanted to mirror what I did, then adhere to the following:
1. DataCamp Data Science with Python track (maybe renamed)...took about 80 hours, but I'm sure the content has changed. Just get through it...it barely made sense at first, but it forces you to start programming right away.
2. Lots of YouTube and Medium (or similar) articles on topics that often overlapped...this helped in my comprehension (loosely follows the "read the textbook 3x" rule).
3. Apply what I learned in the workplace...this was fairly easy because I was essentially a data analyst with a different title. Share with stakeholders the value add. If this doesn't make sense in your job, then make some personal projects and make them public (Github).
4. Learn about incorporating models into a software stack beyond just spinning up Jupyter Notebooks and doing analysis...this became a rabbit hole very quickly...software dev -> computer architecture -> many avenues to go down just learn "enough to be dangerous"
4. Keep learning and be ambitious.
Reach out if you have specific questions
-Cheers
Bowl Leader
I'm putting together a Data Scientist zero to hero repo on my Github. There are several out there already, but I've had friends ask so I'm giving it a whack. It will take some time to put together, but I'll post it here when it's done.
Boot camp for sure. Fastest, cheapest way to make a total switch from a career unrelated to CS/AI into a CS/AI career.