The interview process was professional overall, but I found the take-home component somewhat misaligned with how I would expect senior-level data science work to be evaluated. I invested significant effort into the assignment and approached it as I would a real-world engagement: documenting assumptions and constraints, identifying data quality nuances and ambiguities, communicating tradeoffs, and proposing future improvements beyond the immediate prompt. I focused on analytical rigor, clarity of reasoning, and realistic problem framing rather than simply maximizing output volume. The primary feedback I received was that the submission was “incomplete,” which I personally did not find especially actionable or reflective of the work submitted. In my view, the deliverable addressed the core requirements while also explicitly acknowledging limitations, uncertainties, and areas where additional time or data would have materially improved the analysis. Given the significant time investment involved, I would have appreciated more specific or substantive feedback. I also think candidates should be aware that fully executing the exercise to the apparent level expected may require a level of unpaid time investment that is difficult to balance alongside full-time professional and personal responsibilities. That said, the recruiters and interviewers were courteous throughout the process. In hindsight, the outcome ultimately worked out well for me personally, as I later received opportunities with stronger compensation, better brand value, and organizations whose technical culture aligned more closely with the type of work I’m most interested in long term.