Pros
- Vast variety of problems which requires deep data science to solve it, I have not seen or heard these many unique problems are getting solved at one time by a moderate sized team - Each person owns at least one problem that gives good exposure to solve it end to end, not just research experiments, but also need to make it operational - Real opportunity to learn and keep adding skills with each new problem - Friendly atmosphere to collaborate and strategies problem solution - Ownership driven flat work culture with flexible timings - Well balanced team from research and engineering background supported by academic faculties
Kontras
- Need better office to focus and work efficiently, which is in progress as I know - Weekly talks must happen regularly to share knowledge