Strong colleagues but unclear data science vision and instability
Pros
Smart and capable colleagues across data science, engineering, and product Large-scale data and meaningful business problems (payments, risk, consumer behavior) Good brand name and learning exposure, especially for early-career growth Cross-functional collaboration opportunities are abundant Some teams have strong managers who genuinely support career development
Cons
Product is heavily PM-driven, with limited space for Data Science to proactively shape strategy Lack of a clear data science vision/roadmap, often reacting to product instead of driving it Decision-making can be fragmented, with inconsistent alignment across org layers Frequent org changes and shifting priorities create uncertainty and inefficiency Layoff handling felt abrupt and transactional, with limited transparency or support Visibility and impact can depend heavily on stakeholder relationships rather than actual work quality
