My greatest strength is breaking messy problems into pieces you can actually work on. When something is ambiguous, my instinct is to map it before I touch it.
In my capstone project, my team had a semester to analyze customer churn for a local business, and the dataset was a disaster — three systems, inconsistent fields, no documentation. While the team debated tools, I spent the first week just decomposing the problem: what questions we could answer, what data each one needed, and what to cut. That map became our project plan, and we delivered findings the owner actually used to change her retention emails.
The job posting mentions ambiguous, cross-team data requests — that's exactly the kind of problem I'm best at, because the mapping step is the part most people skip.