It’s extremely hard for someone with master degree to land in a ML position at FAANG in early career. As an alternative, should they go for a DS analytics position at FAANG, which is easier to get in for master? Or should they target for ML positions at a tier2 firm, then change jobs after several years? I see that DS Analytics in FAANG pays more than ML positions at tier2. Is it worth staying at a tier2 for several years just for doing ML? Also is it easy to get into FAANG ML positions after working in tier2 for several years? #datascience #machinelearning
just need to make sure you know that ds analytics at FAANG, especially Facebook, are just sql monkeys, no ML involved
Lot of ds positions in microsoft just deal with just sql/dashboards.
If you want to work on ML, work on ML. If you want to do analytics, do analytics. If you're not sure, take the ML job, easier to move to less technical than to more technical. Moving tier is secondary to know-how once you're in tier 2 on resume. Unless you're after internal transfers, which don't always come with a raise.
Really depends on what you mean by ML. I've worked on a couple of teams that do ML in FAANG. One of them was a science team but most of the work was using rules etc and we rarely published papers. The other team did ML but it wasn't fancy (k-means, random forest etc) so everyone spent at least 80% of time on engineering. so you gotta know if you wanna do ML research or work on ML systems? The former I've heard is getting harder and harder. One way might be to join a FANG as a research engineer and then slowly get to work on the research. If you're interested in the former, I think being a SDE might be more useful than a DS because you need the skill sets to deploy models into production. But I guess this depends on what DS does. The few I've talked to simply do data analytics for business partners and I don't see Engineering managers really looking for people with just that skill set
Yep I think it makes sense. So I’m comparing a DS job at FAANG doing SQL, AB testing type of work vs a ML job at tier2 building and deploying models to product.
Is LinkedIn your tier 2? What ML position did you get? Which team?
LinkedIn is definitely tier 1
I am in the same boat as you are. I have an M.S. Statistics degree and a new grad. I am finding the job market (in LA) is inundated with data analyst roles with the skills other posters mention (SQL, dashboarding) and roles with ML scarce. Currently, I am in a contract role as a dashboarding person using R and Power BI. My other colleagues are having a similar experience.
Which ML positions?