Looking at a Senior Data Scientist position from GoDaddy (Level 3) and ML Engineer (IC3) from Yelp. To add more context, GD role is focussed towards ML experimentations and building impactful trained ML model, and working with Engineers to Ship. Where ML Engineer role is more of your regular MLE role I am assuming. GD and Yelp both 1st year TC: 170 (very similar except couple of thousands). Includes Base, bonus, RSU and Signon Which one has better future career prospects as an ML person? My background is in Applied ML Research with 5YOE. Liked the GD team and manager. As with Yelp I liked how their process is well organized and smooth. Any thoughts? TC: 170
My thoughts are you should post total comp
Its there. I added at the end for better visibility
What does the role entail? At a lot of companies, ML engineering is about shipping code and is similar to general software engineering (but using a different tech stack). Whereas data science is more like a business strategy role where you identify opportunities that will be impactful for the business and don't ship production code. But it's different at every company
To add more context, GD role is focussed towards ML experimentations and building trained ML models solving core business functionality, and working with Engineers to Ship. Where ML Engineer role is more of your regular MLE role.
That sounds like a standard data science role. So the question is, do you want to measure the impact or ship it? Do you want to work to hit metrics goals, or be in charge of defining the metric? And how comfortable are you with working across functions and across teams?
Yelp unless you've daddy issues
Haha.. Any particular reason why yelp ? Curious to know..
Title: MLE > DS Skillset: MLE > DS Pay in long term: MLE > DS If you've a PhD, reject both and try for an RS/AS role. Otherwise, do MLE. As an MLE you learn how to productionize ML models 🔥. DS in most companies is a glorified BA/BIE working with SQL, doing 2 sample t-test for weekly A/B test experiment impact and building toy ML models. As AutoML picks up pace, most of the this work would be automated in future and academic research ML work would become more suitable for RS/AS. On the other hand, with MLE you would get to build skillset of SDE + RS/AS/DS which would remain very high in demand long term. Also, way easier to do MLE -> DS transition that the other way around. Also, Yelp is a better resume brand than GoDaddy.
I worked at both companies. Choose Yelp if you want access to better data, more interesting and challenging projects, and better career prospects.
Quite interesting perspective! Do you mind if I DM you?
I don’t know about yelp, but i wouldn’t recommend that team at godaddy. They seem pretty ineffective and aren’t well respected.
Would you mind connecting on this through DM?
Of course!
In swe, my experience with GoDaddy so far is that people are helpful and resourceful and some of them are very experienced. Good WLB. But things can be slow and you don't feel much going on.
Is this in Canada? I’ll assume it is. 170k CAD TC for IC3 is low in Canada. You can probably negotiate to +200k TC with both GD and Yelp offers. IC3s at Yelp should be getting +200k CAD anyway.
I had no idea! Do you mind if I DM you?
I joined Yelp as IC3 in 2021 and my TC is C$188k (base + annual RSU, bonus not included). You can confidently ask for C$200k+
A bit bias response but hands down Yelp in your case. More interesting data for experimentation. ML is growing and I bet you can have a fasttrack your career too if that’s important to you. I agree with previous mention you can negotiate but even if you don’t get more right away your will grow your comp quicker comparable to anyone long term.
I would personally go for yelp more than GD. GD innovates by buying other companies innovation and everything over time becomes stagnated. Yelp is something like a social network and the data analysis behind it seems a lot more interesting and fluid.
Add a poll? Not in your field but I would vote GD
Good suggestion! Added!
Any reason why would you vote for GD?