While I haven't created formal QA reports in a traditional QA role, I have created detailed analytical reports with similar rigor and structure. At Pluto TV, I created a comprehensive analysis report on our content locking A/B test that documented issues, analyzed impact, and provided actionable recommendations, similar to a QA report's purpose. The report included an executive summary, detailed methodology for analyzing data from 3 million users, key metrics like conversion rates and drop-off patterns broken down by channel, identification of specific problem areas, root cause analysis with supporting data and hypotheses, visual documentation through Tableau dashboards, impact assessment quantifying affected users, and clear recommendations for next steps. I structured it so stakeholders could quickly understand what was working, what wasn't, and why, then make informed decisions about whether to proceed or fix issues before broader rollout. While this was analytical rather than traditional QA documentation, the principles are the same: be thorough, provide evidence, assess impact, and make findings actionable for the teams who need to act on them.

I approach bug identification by staying close to the user experience and looking for patterns, whether that is through user feedback, proactive testing across different scenarios, or analyzing data for anomalies. At my internship at Pluto TV, analyzing viewer complaints taught me that bugs often surface through user reports before internal testing catches them. When documenting bugs, I focus on making them actionable for engineering: clear reproduction steps, expected vs. actual behavior, impact assessment (who's affected and severity), supporting evidence like screenshots or data, and relevant environment details. I also think about prioritization. Not every bug needs immediate fixing, so I consider how many users are impacted, whether there's a workaround, and if it blocks critical flows.