Before you become a data scientist, maybe you have asked your friends or yourself this question: what is a typical day look like as a data scientist? My answer might not be representative enough or general enough, but at least I can give you some idea.
I work in a data science / consulting unit in finance sector. My typical day looks like this:
9:00– come to office / come to my home office during COVID. Get a coffee ready. Open up my Outlook and One Note to get the TODOs.
9:30 ~ 12:00–struggle with bugs in my code, switch between “git pull, git status, git commit, git push” and merge conflict error message.
12:00 ~ 13:00– Lunch. Grab food / restaurants near office. In our company, we have this culture of having lunch appointment with colleagues from other units. This is a good chance to exchange our ideas, share some work / life news, and socialise with other colleagues.
13:00 ~ 18:00– besides the normal coding stuff, there are more meetings (internal or with clients) because afternoon is the overlapping time period across different time zones.
18:00 ~ 19:00– reply some important and urgent emails before I call it a day for my office work.
19:00 ~ 21:00– dinner / take a break
21:00 ~ 23:00 — self-development activities. There are usually the activities I set for myself, like reading books, writing blogs, refreshing on some statistic basics, etc. I found it a good way to keep my knowledge refreshed all the time and be ready to answer any questions whenever I need to.