Ventajas
The WFH culture here is one of the best things. It's not just a policy on paper — it's actually respected. No one's tracking your screen time or pinging you every hour. As long as your work is getting done, you're trusted to manage your own schedule, which makes a huge difference. The projects are solid. I've worked on real ML and data science problems — production systems, not just slides and PoCs. You get to lead things end-to-end if you show the intent, and there's genuine scope to upskill. I've picked up a lot around MLOps, GenAI, and cloud deployment just through the kind of work that comes in. The learning happens on the job, which I personally prefer over mandatory certifications that nobody cares about. Managers here are understanding and approachable. They listen, give you room to execute, and don't get in the way with unnecessary oversight. They also know their domain well enough to have meaningful technical conversations, which is refreshing compared to places where your manager has no idea what you actually do. The overall culture is low on politics and high on getting things done. No fake hustle energy. People are professional, collaborative, and generally easy to work with.
Desventajas
Growth paths for senior folks could be more structured. After a point, it's not always clear what the next step looks like unless you actively push for it. Compensation at the senior level could also be more competitive relative to the market, especially for people handling client delivery and technical leadership.