Pros
- The AI team is genuinely helpful, collaborative, and skilled, their support is invaluable in solving challenges.
Cons
- For data scientists, performance is often judged through political lenses rather than merit, with agendas sometimes undermining genuine contributions. - Data scientists are often given unrealistic deadlines, leading to personal time and weekends being sacrificed, And even after that you will face criticism for partially delivered work, regardless of effort or turnaround time. - When it comes to sharing credit, data scientists are often excluded from communications, but when blame arises, responsibility is shifted to the AI team. - Expected to handle 3–4 projects simultaneously with constant pings from multiple teams, the AI team is heavily overworked, OFTEN continuing to work even during SICK LEAVE. - Every team here wants to jump into AI due to the current boom, but with absolutely zero knowledge or understanding. They'll throw around buzzwords while expecting you to deliver miracles. - QA doesn't know the process how AI models works, they will create tickets for single cases. They expect AI project to be 100% accurate. - The other development team and its leaders have been around for a long time and have known each other since before COVID. The AI team and its leaders are newer and work mostly from home. Favoritism is at its peak, with credit mostly going to the development team, while the AI team is largely ignored, this is 100% true, and you can confirm it with any current or former AI team member on LinkedIn. - Many data scientists starts looking for new jobs within 1–2 months of joining. Join the AI team only if you don't have any other offer. Note: The above points are only for AI Team, In the development team, about 70% of time, employees enjoy a good work-life balance.