You worked on a product or internal analytics problem where a large amount of free text had to be turned into something decision-makers could use. The data may have come from customer feedback, support tickets, survey responses, clinical notes, or another messy text source. You needed to clean the data, choose an NLP approach, and translate model output into useful findings for stakeholders.
Describe a time you applied NLP to extract actionable insights from a large, unstructured dataset.
Ability to frame an unstructured text problem as an NLP pipelineUse of topic modeling, entity extraction, or classification to produce business insightsPractical preprocessing for noisy domain textEvaluation with metrics such as F1 and stakeholder usefulness