Pros
- Great Individuals. No matter what team, there exists super talented and caring individuals in each team - Freedom to experiment various tech stacks, learn and grow - Nice lounge for relaxing, eating and even casual working hours - Good regular events to socialize and bond - Flexible working hours plus home office
Cons
- The most important one is lacking visions in data science projects. After a while you start feeling they are chosen randomly or not thoroughly thought about. Not enough support by stakeholders, at least in my experience. When it is done, it is done in rush with no proper strategy. - It is obvious nowadays that proper execution of a Data Science project needs a good documented data. This is missing. Soon you see yourself immersed in various sources of data, without proper documentations and planned supports. No one is responsible. Someone left a year, did something that largely impacts today's projects. As such building a product in this scenario is super challenging if not impossible. - Decisions made at management level are not discussed openly with team members or team leads. To my witness, this often leads to distrust, & chaos. There is a feedback channel collected quarterly, but no one cares about comments. - In most scenarios, people are underpaid compared to the average market, although management believes otherwise.