**MSFT SWE Intern: SWE vs Data Science**
I’m currently a MSFT SWE Intern and BS Statistics student at a decent state school. I’m not a huge fan of vanilla SWE work and want to work on AI/ML problems as a SWE. Even though there’s no guarantee I do AI/ML stuff in either role, it seems more likely as a data scientist. While coding is meh to me, I like working with numbers & data and using probability & statistics a lot more. However, I’ve also read on Blind that SWEs earn a bit more (on average) than data scientists. Which path would you recommend? Why? Thanks so much!
From what I’ve seen, applied scientists get paid a lot more and tend to have a lot more impact too.
Can you explain further? Also, are you speaking about MSFT specifically or the tech industry in general? I’m trying to decide which to focus on as I will be applying for my final summer (2021) internship this year and need to prep my resume & interviewing skills as such.
Also interested.. how much is the pay bump for applied scientists? (for new grad)
I got my BS in Statistics, but I am very far from being able to work as SWE. Have you been coding for a while?
No, I’m a very novice coder that just likes to solve LC/algo questions in my free time 😛. I’ve definitely learned a lot this summer!
What language are you programming in? Also just out of interest what are some of the things you have learned about writing production level code and of SWE related tasks that are different than just writing python scripts to automate processes (The extent of my non-DS related programming abilities).
OP can I PM you?
Am a ds intern at Microsoft. I think the “data science” label varies greatly. I know some ds interns whose teams just run sql queries. On my team we are doing applied statistical modeling. Part of it is AI, but we do not develop any AI models, we are just the end users. It is pretty intense though. Sometimes feel my background (MS) is not enough since it seems my PhD coworkers are better well-versed in theory and applications than I am. they can skim research papers really quickly whereas I need to read over several times and digest. However I also could never see myself in a vanilla swe role either. At least my current role requires thinking about experimental methodology and applying research, which is interesting. But also tough to keep up. Also, in my team, “ds” vs “swe” seems to be more nomenclature rather than an actual distinction, since we are a stats focused team in the first place
Does microsoft mainly hire Phds for DS internships? Planning on applying in the fall, but the role does seem so diverse (No distinction between DA, DS, AS).
Thanks! Your team sounds awesome! What type of work is specific to the SWE or DS role on your team? I’m guessing SWE may do more data engineering, but I’d guess DS also does this but to a lesser extent.