Avantages
I'd highly, highly recommend the data team AND the applied science team. Since I've joined, Ramp's Data Science team has become a juggernaut. The focus of the team is purely on organizational impact - and like other good data science teams, different members of the team deliver in different ways. This ranges from building infrastructure that truly makes us all 10x faster to well-designed ML to the critical dashboards through which product teams gauge performance. Part of what stands out is how strong the Applied Science team is becoming at using AI. This has been an all-hands-on-deck mandate, and that ranges from building many, many in-product features that use AI, to fine-tuned LLMs, to really smart usage of AI to turn sales and customer interactions into data, to extensive documentation (easily hundreds of pages of docs) to help Claude write code, and thoughtful tools to benchmark AI performance... and that's leaving out more than half of it. The result is that we can just build (high quality) internal and externally facing data products much, much faster - and answer standard data questions much more easily. Ramp's team is so far ahead of the curve that catching up with friends who are strong data scientists at other "best" tech companies is increasingly like going through a time warp back to 2015.
Inconvénients
Ramp is still a startup, just a really big one, and there are lots of ways we're working on the basics, but overall, there aren't many cons. Arguably, getting to work on those basics is a pro. As with many data science roles, you have to be self-guided. You'll be given lots of responsibility and while managers will support you and guide the choice of projects (and give frank feedback), the top performers need to prioritize and communicate. If you can't say "No", you'll struggle. As many people note on Glassdoor, don't come to Ramp if you don't plan to work hard. This is one of those places where you have to be willing to be willing to trade hard work for personal experience. It is possible to have a work-life balance, and managers are extremely understanding of personal demands, but the ideal teammate is interested in the problems we tackle, driven to support the teams we work with, and enthusiastic to build with the rest of us.