Pros
- Compensation and perks are great compared to the market. - Working conditions are nice, with a convenient office, lunches, and snacks. - Having Meta on your resume looks impressive (probably).
Cons
- The focus on impact has created an overly competitive environment. You spend most of your time estimating potential team impact, proving achieved impact, understanding why the impact didn't happen, and competing for impact with others. - Poor skill development opportunities. Data scientists mostly work with SQL, spreadsheets, and write a lot of Google Docs. The tools are mostly internal, so there's little exposure to common open-source tools and almost no Machine Learning. - There is a lot of bureaucracy and time spent on alignment. Middle management is often useless, spending most of their time in meetings and ticking boxes for their PSC rather than managing, doing useful work and caring for their teams.
