I’ve found this to be one of the more misunderstood questions among aspiring data scientists. A LOT of folks believe that they’ll be working on building and tweaking models all day - which simply isn’t the case (for most of us anyway!). I personally find myself working with all sorts of messy data which means data cleaning takes up most of my time.
What has your experience been like? Or what do you feel it should be? Would love to hear the thoughts of the community.
This thread is inspired by the below article which covers 5 answers from leading data scientists. Each answer brings a different perspective to the table. A data scientist’s role is truly a multi-faceted one!
Check out the article here: